Method for constructing waiting area road in map, vehicle and cloud server

Abstract

The invention relates to a method for constructing a waiting area road in a map, a vehicle and a cloud server. The method comprises the steps that historical vehicle uploading data are acquired, and the historical vehicle uploading data comprise intersection semantic information, uploaded by historical vehicles, of roads in a waiting area and historical vehicle driving tracks; generating waiting area road structure information according to the intersection semantic information and the historical vehicle driving track; and in response to the received positioning information and / or navigation route information reported by the target vehicle, issuing the waiting area road structure information to the target vehicle, so that the target vehicle displays the waiting area road structure information. According to the invention, the technical problems of low recognition efficiency and poor accuracy when the road in the waiting area in the intersection area is recognized in the prior art are solved.

Description

Technical Field

[0001] The present disclosure relates to the field of autonomous driving technology, and in particular to a method for constructing a road in a waiting area in a map, a vehicle, and a cloud server. Background Art

[0002] During the driving process, autonomous vehicles will pass through various types of intersections. For example, in order to improve the traffic efficiency of intersections, some intersections have waiting areas. Before the green light comes on, vehicles are allowed to enter the waiting area in advance and queue up. After the green light comes on, vehicles can pass through the intersection more quickly to improve traffic efficiency and reduce traffic congestion. Therefore, accurate identification of the waiting area road structure is crucial to improving the autonomous driving experience. In the relevant technology, in the scenario of high-precision map coverage, the waiting area road structure information in the high-precision map can be directly used, but the coverage area of ​​the high-precision map is extremely limited due to high costs and other reasons.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] The disclosed embodiments provide a method, a vehicle, and a cloud server for constructing a waiting area road in a map, so as to at least solve the technical problems of low recognition efficiency and poor accuracy in the related art when identifying the waiting area road in the intersection area.

[0005] According to one aspect of the embodiments of the present disclosure, a method for constructing a road in a waiting area in a map is provided, comprising: obtaining historical vehicle uploaded data, wherein the historical vehicle uploaded data comprises: intersection semantic information of the road in the waiting area uploaded by historical vehicles and historical vehicle driving trajectories; generating road structure information in the waiting area according to the intersection semantic information and historical vehicle driving trajectories; in response to receiving positioning information and / or navigation route information reported by a target vehicle, sending the road structure information in the waiting area to the target vehicle, so that the target vehicle displays the road structure information in the waiting area.

[0006] According to another aspect of the embodiment of the present disclosure, a vehicle for constructing a road in a waiting area in a map is also provided, including: a sending module for sending positioning information and navigation route information of the vehicle to a cloud server; a receiving module for receiving road structure information of the waiting area sent by the cloud server, wherein the road structure information of the waiting area is road structure information of the waiting area at a waiting intersection within a preset distance from the positioning information; and a display module for displaying the road structure information of the waiting area on a graphical user interface of the vehicle.

[0007] According to another aspect of the embodiment of the present disclosure, a vehicle for constructing a waiting area road in a map is also provided, including: a sending module for sending navigation route information of the vehicle to a cloud server; a receiving module for receiving all the waiting area road structure information on the navigation route issued by the cloud server; a matching module for matching corresponding waiting area road structure information from all the waiting area road structure information based on the vehicle's positioning information, wherein the corresponding waiting area road structure information is the waiting area road structure information of the waiting intersection within a preset distance from the positioning information; and a display module for displaying the waiting area road information corresponding to the positioning information on a graphical user interface of the vehicle.

[0008] According to another aspect of the embodiment of the present disclosure, a vehicle for constructing a waiting area road in a map is also provided, including: a sending module for sending the vehicle's positioning information and navigation route information to a cloud server; a receiving module for periodically receiving a preset number of waiting area road structure information issued by the cloud server, wherein the waiting area road structure information is the waiting area road structure information of the waiting intersection on the navigation route; a matching module for matching corresponding waiting area road structure information from a preset number of waiting area road structure information based on the vehicle's positioning information, wherein the corresponding waiting area road structure information is the waiting area road structure information of the waiting intersection within a preset distance from the positioning information; a display module for displaying the waiting area road information corresponding to the positioning information on a graphical user interface of the vehicle.

[0009] According to another aspect of an embodiment of the present disclosure, a vehicle for constructing a road in a waiting area in a map is also provided, including: an acquisition module for acquiring the vehicle's positioning information, navigation route information and vehicle historical data in a storage module, wherein the vehicle historical data includes: intersection semantic information and historical driving trajectories of the road in the waiting area; a generation module for generating structure information of the road in the waiting area according to the intersection semantic information and the historical driving trajectories; a matching module for matching the corresponding structure information of the road in the waiting area based on the positioning information and the navigation route information; and a display module for displaying the structure information of the road in the waiting area on a graphical user interface of the vehicle.

[0010] According to one aspect of the embodiments of the present disclosure, there is also provided a cloud server, comprising: a processor; a memory for storing processor executable instructions; wherein the processor is configured to execute instructions to implement the methods in various embodiments of the present disclosure.

[0011] According to one aspect of the embodiments of the present disclosure, a computer-readable storage medium is further provided, the computer-readable storage medium including a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present disclosure.

[0012] According to one aspect of the embodiments of the present disclosure, a computer program product is also provided, including a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present disclosure is implemented.

[0013] According to one aspect of the embodiments of the present disclosure, a computer program product is also provided, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present disclosure is implemented.

[0014] According to one aspect of the embodiments of the present disclosure, a computer program is further provided. When the computer program is executed by a processor, the methods in the various embodiments of the present disclosure are implemented.

[0015] In the disclosed embodiment, by acquiring historical vehicle upload data, the historical vehicle upload data includes intersection semantic information of the waiting area road uploaded by the historical vehicle and the historical vehicle driving trajectory, and then generating the waiting area road structure information according to the intersection semantic information and the historical vehicle driving trajectory, and finally in response to receiving the positioning information and / or navigation route information reported by the target vehicle, the waiting area road structure information is sent to the target vehicle, so that the target vehicle can display the waiting area road structure information, thereby helping the target vehicle to better understand the situation of the waiting area road in the waiting area road, thereby improving driving safety and intersection traffic efficiency. At the same time, by sending the waiting area road structure information to the target vehicle for display, the automatic driving system can effectively improve the recognition and planning capabilities of the waiting area road, reduce the complexity of real-time perception, and optimize the driving experience. The method for constructing the waiting area road in the map provided by the disclosed embodiment can improve the recognition efficiency and accuracy of the waiting area road in the intersection area, while reducing the calculation load, optimizing the driving experience, and thus solving the technical problems of low recognition efficiency and poor accuracy in the related technology when identifying the waiting area road in the intersection area. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present disclosure and constitute a part of the present disclosure. The illustrative embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation on the present disclosure. In the drawings: Figure 1 is a flow chart of a method for constructing a road in a waiting area in a map according to one embodiment of the present disclosure; Figure 2 is a schematic diagram of intersection semantic information according to one embodiment of the present disclosure; Figure 3 is a schematic diagram of an intersection area according to one embodiment of the present disclosure; Figure 4is another schematic diagram of an intersection area according to one embodiment of the present disclosure; Figure 5 is a schematic diagram of an associated adsorption process according to one embodiment of the present disclosure; Figure 6 is a schematic diagram of road structure information of a waiting area according to one embodiment of the present disclosure; Figure 7 is a schematic diagram of a process for generating a center line of a waiting area according to one embodiment of the present disclosure; Figure 8 is a structural block diagram of a vehicle for constructing a road in a waiting area in a map according to one embodiment of the present disclosure; Fig. 9 is a structural block diagram of another vehicle for constructing a road in a waiting area in a map according to one embodiment of the present disclosure; Fig.10 is a structural block diagram of another vehicle for constructing a road in a waiting area in a map according to one embodiment of the present disclosure; Fig.11 It is a structural block diagram of another vehicle for constructing a road in a waiting area in a map according to one embodiment of the present disclosure. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the scheme of the present disclosure, the technical scheme in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present disclosure.

[0018] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0019] According to an embodiment of the present disclosure, an embodiment of a method for constructing roads in a waiting area in a map is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0020] The method embodiment can be executed in an electronic device or a similar computing device including a memory and a processor. Taking running on a computer terminal as an example, the computer terminal may include one or more processors (processors may include but are not limited to central processing units (CPU), graphics processing units (GPU), digital signal processing (DSP) chips, microprocessors (MCU), programmable logic devices (Field Programmable Gate Array, FPGA), neural network processors (Neural-network Processor Unit, NPU), tensor processors (TensorProcessing Unit, TPU), artificial intelligence (Artificial Intelligence, AI) type processors and other processing devices) and a memory for storing data. Optionally, the above-mentioned computer terminal may also include a transmission device, an input and output device, and a display device for communication functions. It can be understood by those skilled in the art that the above-mentioned structural description is only for illustration and does not limit the structure of the above-mentioned computer terminal. For example, the computer terminal may also include more or fewer components than the above-mentioned structural description, or have a configuration different from the above-mentioned structural description.

[0021] The memory can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the method for constructing roads in the waiting area in the map in the embodiment of the present disclosure. The processor executes various functional applications and data processing by running the computer program stored in the memory, that is, the method for constructing roads in the waiting area in the map is realized. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory may further include a memory remotely arranged relative to the processor, and these remote memories can be connected to the mobile terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0022] The transmission device is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0023] The display device may be, for example, a touch screen type liquid crystal display (LCD) and a touch display (also referred to as a "touch screen" or "touch display screen"). The liquid crystal display may enable the user to interact with the user interface of the mobile terminal. In some embodiments, the mobile terminal has a graphical user interface (GUI), and the user may interact with the GUI by finger contacts and / or gestures on the touch-sensitive surface. The human-computer interaction functions here may optionally include the following interactions: creating web pages, drawing, word processing, making electronic documents, games, video conferencing, instant messaging, sending and receiving emails, call interfaces, playing digital videos, playing digital music and / or web browsing, etc. The executable instructions for executing the above human-computer interaction functions are configured / stored in a computer program product or readable storage medium executable by one or more processors.

[0024] Figure 1 is a flow chart of a method for constructing a road in a waiting area in a map according to one embodiment of the present disclosure, such as Figure 1 As shown, the method comprises the following steps: Step S11, obtaining historical vehicle uploaded data, wherein the historical vehicle uploaded data includes: intersection semantic information of the waiting area road uploaded by historical vehicles and historical vehicle driving tracks; Step S12, generating road structure information of the waiting area according to intersection semantic information and historical vehicle driving trajectories; Step S13, in response to receiving the positioning information and / or navigation route information reported by the target vehicle, the road structure information of the waiting area is sent to the target vehicle, so that the target vehicle displays the road structure information of the waiting area.

[0025] The method for constructing a road in a waiting area in a map provided in the embodiments of the present disclosure can be applied to a low-precision map, which is a type of map data used for basic navigation and path planning, and contains basic information of a road network, such as the location of roads, lane directions, names, intersections, and highway entrances and exits. Compared with high-precision maps, low-precision maps have lower information accuracy and detail, and the format and structure of the stored data are relatively simple, easy to store and transmit, and suitable for most consumer-level navigation devices and applications.

[0026] In an optional embodiment, the waiting area road includes at least one of the following: a left-turn waiting area road, a right-turn waiting area road, and a straight-ahead waiting area road. The left-turn waiting area road and the right-turn waiting area road can also be alternatively described as a waiting area road. Each type of waiting area road has a specific geometric layout and traffic rules. Therefore, the differences in the amount of different types of roads need to be taken into account during construction, so as to provide more accurate guidance for the autonomous driving vehicle or driver.

[0027] Specifically, at urban intersections, especially in busy traffic environments, the setting of left-turn waiting area roads can effectively improve traffic fluidity and safety. For example, when constructing a left-turn waiting area road, it is necessary to identify the specific location and boundaries of the left-turn lane, the left-turn stop line, the left-turn indicator light, and the left-turn waiting area. In particular, the left-turn waiting area is usually located on the left side of the intersection, adjacent to the straight or right-turn lanes of the opposite direction, so the relative position relationship with the opposite lane also needs to be considered during construction.

[0028] Similar to the left-turn waiting area, the construction of the right-turn waiting area also requires the identification of the right-turn lane, stop line, indicator light, and waiting area boundary, but its layout and traffic rules are different from those of the left-turn waiting area. For example, the right-turn waiting area does not require special indicator light control, but is achieved through the control of conventional traffic lights. In addition, the geometry of the right-turn waiting area is more complex, and special scenarios such as curves and narrow intersections need to be handled.

[0029] In some cases, through lanes also require waiting areas, especially at large intersections or areas with complex traffic flows. When constructing through waiting area roads, attention should be paid to the stop line of the through lane, the boundary of the through waiting area, and any traffic elements that may affect the travel of through vehicles, such as bus lanes, insertion points of right turn lanes, etc. The construction of through waiting area roads may focus more on the straightness and efficiency of the route to reduce the waiting time of through vehicles at intersections and increase the speed of travel.

[0030] It should be noted that the waiting area road is taken as the waiting area road in the embodiment of the present application for illustration, but it does not constitute a specific limitation on the waiting area road. The waiting area road is usually designed in urban traffic intersections, especially to improve the traffic efficiency and driving safety of the intersection. The waiting area road has a specific geometric layout and signs to guide vehicles to enter a specific area while waiting for the green light, so that they can pass the intersection more quickly and orderly when the signal light turns green.

[0031] Exemplarily, the straight waiting area road is usually rectangular, and the boundary lines of the straight waiting area are generally composed of bold or specially marked lane lines, which frame the rectangular area and clearly indicate when the driver can enter the waiting area to wait. At the entrance of the straight waiting area, there will be a stop line (usually a solid line), and the vehicle must stop behind this line when the light is red until it receives the signal to enter the waiting area. The straight waiting area is usually controlled by traffic lights, and sometimes a special straight indicator light is set to indicate that straight vehicles can enter the waiting area and wait for the green light. In the straight waiting area, there can be a guide arrow sign to indicate the direction in which the vehicle is waiting and the way to go when the light is green, to ensure that the vehicles are correctly arranged in the waiting area and avoid wrong travel.

[0032] For example, the road in the waiting area is usually fan-shaped or in a special shape, located near the turning lane at the intersection, and separated from the straight lane. The road in the waiting area can have special lane lines, stop lines, and guide arrows. For example, the boundary of the road in the waiting area can be marked by bold lane lines or lane lines with special marks (such as zigzags) to distinguish it from ordinary lanes. The traffic lights at the intersection can allow vehicles to enter the waiting area road to wait in a specific traffic mode (such as left turn, right turn).

[0033] Low-precision maps can provide relatively low-precision road information, usually including the basic direction of the road, intersection location, road type and simple navigation information. Low-precision maps are mainly used for basic route planning and navigation, and do not contain detailed information and specific layout of the roads in the waiting area. In low-precision maps, complex intersection structures may be simplified, lacking the specific location and shape description of lane lines and stop lines in the waiting area, as well as control information of traffic lights. As a result, the navigation system or automatic driving assistance system that only relies on low-precision maps in related technologies cannot provide accurate guidance for entering the waiting area. When the vehicle approaches a complex intersection, it needs to rely on a real-time perception system to supplement these key details.

[0034] The embodiment of the present application can not only expand the application scope of autonomous driving technology and reduce the implementation cost by constructing and displaying the road in the waiting area in the low-precision map, but also ensure driving safety to a certain extent, improve the driving experience, and promote technology iteration and progress. Specifically, due to the high production and maintenance costs of high-precision maps and limited coverage, the widespread application of autonomous driving technology is limited. Using low-precision maps to construct the road structure of the waiting area can reduce the hardware and software costs of the autonomous driving system, enable more models and scenarios to achieve autonomous driving, and promote the popularization of technology. In addition, even under low-precision map conditions, accurate identification of the road structure of the waiting area can guide autonomous driving vehicles to drive safely at intersections and reduce the risk of traffic violations and accidents caused by road structure recognition errors. By extracting road semantic information from lightweight data uploaded by historical vehicles, the lack of details in low-precision maps can be compensated, providing vehicles with more reliable driving guidance. The accurate construction of the road structure information of the waiting area helps vehicles plan turning paths in advance, further improving driving smoothness and experience.

[0035] The above-mentioned historical vehicles may be vehicles that have traveled on some sections or intersections of the target vehicle's self-driving navigation route (hereinafter referred to as the waiting area road) and uploaded lightweight data to the cloud before the target vehicle turned on the self-driving function. The vehicle may be other vehicles or the target vehicle. If the target vehicle has traveled on the waiting area road before, the historical vehicle uploaded data may be data uploaded to the cloud server by the target vehicle after the past travel. In autonomous driving and intelligent transportation systems, the lightweight data uploaded by historical vehicles becomes a key source of information for analyzing road conditions, identifying traffic signs, and building road structure models. Historical vehicle data can not only be used for path planning and navigation of the target vehicle, but also provide future vehicles with prior knowledge about the road section, so that subsequent vehicles can travel more accurately and safely.

[0036] Specifically, during driving, historical vehicles can upload road information and obstacle information, where road information includes but is not limited to lane lines, road signs, traffic lights, road signs, etc., and obstacle information includes but is not limited to static obstacles (such as buildings, roadblocks, etc.) and dynamic obstacles (such as moving vehicles, pedestrians, etc.). The acquisition of data uploaded by historical vehicles usually relies on the data exchange mechanism established between historical vehicles and cloud servers. During driving, historical vehicles collect road environment information around the roads they pass through through on-board sensors such as on-board cameras, radars, and lidars, and upload it to the cloud server at an appropriate time, such as uploading it to the cloud at night when the user is not using the car. For example, when a historical vehicle passes through the waiting area road, the on-board sensors can capture road environment information including but not limited to: lane lines, stop lines, pedestrian crossings, traffic signs and lights, road layout, etc. Among them, lane lines mainly involve the type (solid line, dotted line), position and road direction of road markings; stop lines are the position of parking lines, usually located near pedestrian crossings; pedestrian crossings involve the position and shape of pedestrian crossing areas; traffic signs and signal lights involve traffic rules at intersections, including speed limits, direction instructions, etc.; road layout involves the type of intersections (such as T-shaped, cross-shaped), lane branches, etc. The above information is collected by sensors of historical vehicles, processed and analyzed by on-board computers, and refined into key semantic features, uploaded to the cloud for subsequent analysis and application.

[0037] The above historical vehicle upload data includes the intersection semantic information of the waiting area road uploaded by the historical vehicle and the historical vehicle driving trajectory. Specifically, the intersection semantic information of the waiting area road refers to the road environment information captured by the historical vehicle through its on-board sensor on the waiting area road and the straight waiting area road, and the intersection semantic information is filtered out from the road environment information. The intersection semantic information includes at least the first stop line, the crosswalk, 2 branch lane lines, and the second stop line. The first stop line is close to the crosswalk and is a line along the navigation route that has not passed the crosswalk. The second stop line is the stop line after passing the crosswalk along the navigation route, and is located on the waiting area road or the straight waiting area road. The historical vehicle driving trajectory records the driving path of the vehicle on the road, and usually includes the location coordinates, driving direction and other information of the historical vehicle. Specifically, it can be positioning data provided by the Global Positioning System (GPS), it can be positioning data provided by the BeiDou Navigation Satellite System (BDS), or it can be the result of precise positioning combined with vehicle sensor data, which will not be listed one by one here.

[0038] For example, the historical vehicle can directly filter and process the road environment information collected by its own sensor to obtain the intersection semantic information of the road in the waiting area, and then upload the intersection semantic information of the road in the waiting area and the historical vehicle driving trajectory to the cloud server. In this process, on the one hand, the delay of data transmission and processing can be reduced, so that the cloud server can obtain the latest intersection semantic information more quickly. On the other hand, by uploading lightweight intersection semantic information, the amount of transmitted data is significantly reduced, thereby effectively reducing the cost and bandwidth requirements of data transmission, so that the method in the embodiment of the present disclosure can be effectively operated even in low bandwidth or unstable network conditions.

[0039] Exemplarily, after obtaining the historical vehicle uploaded data, first, the large amount of data uploaded by the historical vehicles is preprocessed, including but not limited to format unification, noise removal and data calibration, to ensure that the processed data is of high quality and consistent. Preferably, intersection semantic information with good timeliness is screened out from the historical vehicle uploaded data. For example, priority is given to lane lines that contain clear waiting areas. Decisions based on outdated data will lead to a lag effect, that is, there is a time difference between the road condition information and the actual road condition, which affects driving safety and experience. Therefore, the intersection semantic information closest to the current time is given priority to accurately reflect the actual conditions of the current waiting area road, which can further improve the response speed and safety performance of the autonomous driving system.

[0040] Exemplarily, the information from multiple filtered data sources is fused, and the accuracy of the extracted intersection semantic information is ensured through cross-validation and consistency checks. If the historical vehicle uploaded data comes from different time points or different perspectives, the fusion process can further improve the integrity and accuracy of the information. In order to obtain intersection semantic information more accurately, the screening criteria and algorithms can be continuously optimized. For example, thresholds can be set to exclude noise or abnormal data, and machine learning algorithms can be used to automatically identify and filter high-quality data. The data with richer filtered road elements can not only provide a more solid foundation for the automatic construction of the road structure in the waiting area, but also help the autonomous driving system to better understand and adapt to complex intersection environments, thereby improving driving safety and efficiency. Through this series of screening and optimization, the accuracy and completeness of the intersection semantic information can be ensured, providing a high-quality reference for the subsequent construction of the road structure in the waiting area and autonomous driving decisions.

[0041] After obtaining the intersection semantic information of the waiting area road, the waiting area road structure information can be generated based on the intersection semantic information and the historical vehicle driving trajectory. The above-mentioned waiting area road structure information can provide the autonomous driving system with a detailed structural description of the waiting area intersection, and is also the basis for the target vehicle to plan and make decisions on the path. Using the waiting area road structure information, the vehicle side can plan the best driving route through complex intersections in advance, including details such as when to slow down, when to turn, and when to wait, so as to ensure the safety and smoothness of driving. In the existing technology, the key traffic sign elements near the intersection of the waiting area can be identified by relying on the real-time perception data of the vehicle, so as to reconstruct and update the road structure of the waiting area in real time. However, due to the influence of various factors such as limited real-time perception sight distance, traffic obstruction, and interference from guide lines, the real-time key sign elements on the vehicle side will often be misjudged, missed, and incompletely perceived, resulting in errors and delays in the identification of the road structure of the waiting area, making it impossible for the vehicle in assisted driving to pass the intersection as expected. In serious cases, it is even prone to collision risks. This solution obtains the road structure information of the waiting area in advance. When the target vehicle approaches the intersection of the waiting area, it can reduce the dependence on real-time perception technology and reduce the driving risks caused by the lack or error of real-time perception information. Even in low visibility or complex road conditions, the vehicle can make accurate judgments based on prior information. The key elements in the road structure information of the waiting area can be used as a positioning reference to help the vehicle more accurately determine its position on the road and further enhance the autonomous driving experience.

[0042] The above-mentioned waiting area road navigation information may include detailed operation guidelines for the target vehicle to pass through the intersection area, such as steering suggestions, driving speed, and areas to be avoided, etc., to provide clear guidance for the driver or the automatic driving system to ensure that the intersection is passed in a regular and safe manner. The waiting area road navigation information can also warn the driver or the automatic driving system in advance about the existence and entry conditions of the waiting area intersection. For example, when the vehicle approaches the waiting area in the intersection, a prompt to slow down or prepare to turn can be issued. Based on a deep understanding of the intersection structure, the waiting area road navigation information can help the target vehicle optimize the driving strategy, such as adjusting the acceleration and deceleration timing, ensuring that the turn is made at the correct position, etc., thereby improving driving efficiency and reducing unnecessary waiting and driving time. The intersection navigation route provided in the related art is only a right-angle turn, which only serves to mark the turn, rather than a reasonable intersection passage path. The waiting area road navigation information generated in the embodiment of the present disclosure not only identifies the change in driving direction, but also can give accurate turning timing and angle suggestions according to the specific layout of the waiting area. For example, in a complex intersection, the driver can be informed in advance when to start preparing to turn, as well as the specific turning angle, to avoid unsafe or non-compliant driving caused by blind turning. By analyzing historical driving trajectories, it can also predict and recommend the smoothest turning path, avoiding sharp turns or turning at inappropriate locations, thereby reducing the impact on other traffic participants.

[0043] In summary, the road structure information in the waiting area is mainly used to construct the decision-making logic framework for vehicles passing through complex intersections, while the road navigation information in the waiting area focuses on providing specific operation guidance and safety tips for the actual driving process. The two can work together to ensure the safe and efficient passage of the target vehicle at the intersection of the waiting area.

[0044] For example, in the vehicle driving mode, the target vehicle mainly relies on the autonomous driving system to control driving, and the road structure information of the waiting area is crucial to the autonomous driving system. By combining the intersection semantic information with the historical vehicle driving trajectory, a detailed waiting area road can be constructed, which helps the autonomous driving system to accurately understand and predict the use of the waiting area, including when it is safe to enter the waiting area, how to act according to the status of traffic lights, and how to avoid conflicts with other vehicles or pedestrians. The road structure information of the waiting area can also optimize path planning to ensure that the vehicle can follow the best driving strategy in complex intersection environments, thereby improving the safety and user experience of autonomous driving.

[0045] For another example, in the driver's self-driving mode, the driver is mainly responsible for driving the target vehicle, and the waiting area road structure information and waiting area road navigation information can provide strong support for the driver. Based on the intersection semantic information and historical vehicle driving trajectories, a clear description of the intersection layout can be given, including the scope of the waiting area, the direction of the lane line, the specific location of the stop line, the distribution of crosswalks, and any special road sign information. The waiting area road navigation information can also provide traffic rule reminders, recommended driving routes, potential traffic congestion prompts, and optimal turning time suggestions. For drivers, the waiting area road structure information and waiting area road navigation information can enhance their understanding of road conditions, help predict traffic conditions, and make safer and more efficient driving decisions. The waiting area road navigation information can be conveyed to the driver through the vehicle's navigation system, dashboard display, voice prompts, and other methods to ensure the timeliness and ease of use of the information.

[0046] When the positioning information and / or navigation route information reported by the target vehicle is received, the road structure information and / or navigation information of the waiting area can be sent to the target vehicle, so that the target vehicle can display the road structure information and / or navigation information of the waiting area. Specifically, after the cloud server receives the real-time positioning information and navigation route information of the target vehicle, it will match the relevant road structure information and navigation information of the waiting area according to the current position and destination of the target vehicle to ensure that the information sent is the road structure information and / or navigation information of the waiting area for the target vehicle to pass the intersection.

[0047] For example, in order to ensure that the road structure information of the waiting area can be correctly parsed by the target vehicle, the cloud server can convert the road structure information of the waiting area into a data format understood by the vehicle, such as a standard navigation data packet or specific vehicle system protocol data, to facilitate rapid consumption and display on the vehicle side.

[0048] After the target vehicle receives the road structure information of the waiting area sent by the cloud server, the on-board display system will display the road structure information of the waiting area to the driver in an intuitive way, such as displaying the detailed layout of the intersection, the lanes and guide arrows in the waiting area, the location of the stop line, etc. on the on-board navigation screen. At the same time, the automatic driving system will use the information sent to perform real-time path planning and decision-making to ensure that the target vehicle passes the intersection safely according to the expected route. In this way, the target vehicle can obtain accurate information about complex intersections in advance, which greatly improves the safety and efficiency of vehicles passing through the waiting area intersection, whether it is to provide intuitive driving guidance to the driver or to provide decision-making basis for the automatic driving system.

[0049] For example, the cloud server can also continuously monitor the updated information of the roads in the waiting area, such as road construction, changes in traffic rules, etc., and update the structural information and navigation information in a timely manner. When new information is generated, it will be immediately sent to the target vehicle through the vehicle-cloud communication system to ensure that the target vehicle can respond to road changes in a timely manner. After consuming the information, the target vehicle can feedback the new situations encountered during actual driving to the cloud, forming a closed loop of information and further optimizing the cloud service. The dynamic update mechanism of the cloud can ensure the real-time and accuracy of the information, so that it can remain effective in a constantly changing traffic environment.

[0050] Based on the above steps S11 to S13, by acquiring historical vehicle upload data, the historical vehicle upload data includes the intersection semantic information of the waiting area road uploaded by the historical vehicle and the historical vehicle driving trajectory, and then generating the waiting area road structure information according to the intersection semantic information and the historical vehicle driving trajectory, and finally in response to receiving the positioning information and / or navigation route information reported by the target vehicle, the waiting area road structure information is sent to the target vehicle, so that the target vehicle can display the waiting area road structure information, thereby helping the target vehicle to better understand the situation of the waiting area road in the waiting area road, thereby improving driving safety and intersection traffic efficiency. At the same time, by sending the waiting area road structure information to the target vehicle for display, the automatic driving system can effectively improve the recognition and planning capabilities of the waiting area road, reduce the complexity of real-time perception, and optimize the driving experience. The method for constructing the waiting area road in the map provided by the embodiment of the present disclosure can improve the recognition efficiency and accuracy of the waiting area road in the intersection area, while reducing the calculation load, optimizing the driving experience, and thus solving the technical problems of low recognition efficiency and poor accuracy in the related technology when identifying the waiting area road in the intersection area.

[0051] It should be noted that the method for constructing a road in a waiting area in a map in the embodiment of the present application can be executed by either a cloud server or a target vehicle. Through flexible execution modes, intelligent transportation systems and autonomous driving technologies can better adapt to various road conditions and communication environments, providing users with a more reliable, efficient and safe driving experience.

[0052] For example, when the cloud server interacts with the target vehicle, since the cloud server usually has more powerful computing resources and data processing capabilities, it can process a large amount of data from multiple vehicles at the same time, perform complex algorithm operations and data analysis, and thus more accurately construct the road structure of the waiting area. By aggregating the information uploaded by multiple historical vehicles, the cloud server can obtain more comprehensive intersection semantic information, which helps to build a more accurate road structure model. At the same time, the cloud can quickly update and adjust map data to ensure that all vehicles can receive the latest road information. In addition, the cloud is responsible for building and updating the road structure of the waiting area, which can reduce the data storage requirements and computing load on each vehicle, and facilitate unified data maintenance and management. The process of interactive execution by the cloud server and the target vehicle can be specifically applicable to areas with good high-precision map coverage and real-time communication environment, such as city centers or highways, or fleet operation scenarios that require global map updates and management, such as taxi or shared car services.

[0053] The following is a further introduction to the method for constructing roads in the waiting area in the map in the embodiment of the present disclosure.

[0054] In an optional embodiment, the intersection semantic information includes: a first stop line, a second stop line, a crosswalk area, and candidate branch lane lines, wherein the first stop line is used to represent the stop line of the straight lane of the waiting area road, and the second stop line is used to represent the stop line associated with the candidate branch lane line.

[0055] Take the left-turn waiting area road as an example. Figure 2 is a schematic diagram of intersection semantic information according to one embodiment of the present disclosure, such as Figure 2 As shown in the figure, at an intersection with a left-turn waiting area, the first stop line is the stop line of the straight lane of the waiting area road, located at the end of the straight lane. When the traffic light is red, straight and left-turning vehicles must stop behind this line. The first stop line is usually composed of a conspicuous solid line sign to ensure that the driver clearly knows the driving stop position.

[0056] The second stop line is the stop line associated with the candidate branch lane line. Historical vehicles can enter the left turn waiting area after passing through the pedestrian crossing area from the straight lane of the left turn waiting area. Figure 2The candidate branch lane lines in can be the lane lines at the left and right boundaries of the left turn waiting area. The second stop line is located at the end of the road in the left turn waiting area. Usually, when the traffic light of the straight lane is red, and the traffic light of the left turn lane shows a specific left turn waiting indication (such as a flashing arrow or text message), the left-turning vehicle can cross the first stop line and the crosswalk area, enter the left turn waiting area and wait, and needs to stop behind the second stop line until the left turn signal turns green.

[0057] In an optional embodiment, in step S12, generating the road structure information of the waiting area according to the intersection semantic information and the historical vehicle driving trajectory includes: Step S121, filtering and processing the historical vehicle uploaded data to obtain the first stop line and the crosswalk area; Step S122, searching and processing lane lines within a preset range near the first stop line based on the first stop line and the crosswalk area, and obtaining lane line search results and stop line search results; Step S123, filtering and processing are performed according to the lane line search results and the stop line search results to obtain the lane lines of the waiting area; Step S124, screening the lane lines in the waiting area based on the historical vehicle driving trajectory to obtain candidate branch lane lines; Step S125, determining at least one target waiting area using the candidate branch lane lines; Step S126: Generate road structure information of the waiting area according to at least one target waiting area.

[0058] Figure 3 is a schematic diagram of a road intersection area according to one embodiment of the present disclosure, such as Figure 3 As shown, the first stop line and the pedestrian crossing area are screened out from the historical vehicle upload data, so as to ensure that the first stop line and the historical vehicle driving trajectory are close to or intersect for the first time. For example, for the first stop line, an edge detection algorithm or a feature matching algorithm can be used to identify the line; for the pedestrian crossing area, a specific texture or pattern can be found, such as the black and white stripes of a zebra crossing.

[0059] Figure 4 is another schematic diagram of an intersection area according to one embodiment of the present disclosure, such as Figure 4As shown, the intersection is a crossroads, including roads in four intersection directions: A, B, C, and D. Each road is usually composed of multiple lanes, including a straight lane, a left turn lane, and a right turn lane. Some roads may also include bus lanes, bicycle lanes, and sidewalks. After filtering and processing the historical vehicle uploaded data to obtain the first stop line and the crosswalk area, all lane lines and stop lines are searched within the preset area in front of and on both sides of the first stop line. For example, in the process of searching for lane lines, the lane lines can be detected and identified for the image data or radar point cloud data uploaded by the historical vehicle. The type (solid line, dotted line), direction, and continuity of the lane lines need to be considered in the identification process. In the process of searching for stop lines, it is usually based on the geometric shape, position, and direction of the lines to ensure that the detected stop line is consistent with the identified first stop line in terms of geometric relationship. Taking intersection A as an example, a search is performed within the preset area in front of and on both sides of the first stop line. The searched lines include all lane lines and stop lines at intersection B opposite intersection A, all lane lines and stop lines at intersection C in the left turn direction, all lane lines and stop lines at intersection D in the right turn direction, and the long diagonal lines in the intersection.

[0060] Further, according to the lane line search results and the stop line search results, the lane lines in the waiting area are obtained. The lane lines in the waiting area include the lane lines in the waiting area for turning and the lane lines in the straight waiting area in the same road direction. Figure 4 For example, based on the search results of the lane line and the stop line of intersection A, the lane lines in the directions of intersections B, C, and D can be filtered out, and the lane lines of the left turn waiting area and the straight going waiting area in the direction of intersection A can be retained.

[0061] Furthermore, based on the historical vehicle driving trajectory, the lane lines in the waiting area are screened and processed to obtain candidate branch lane lines, and the candidate branch lane lines can be lane lines in the left-turn waiting area or lane lines in the straight-ahead waiting area. In an optional embodiment, based on the historical vehicle turning driving trajectory, the lane lines in the waiting area can be filtered out, thereby obtaining candidate branch lane lines for turning left in the direction of intersection C, and the candidate branch lane lines match the turning driving trajectory. In another optional embodiment, based on the historical vehicle straight-ahead driving trajectory, the lane lines in the waiting area can be filtered out, thereby obtaining candidate branch lane lines for going straight in the direction of intersection B, and the candidate branch lane lines match the straight-ahead driving trajectory.

[0062] At least one target waiting area is determined by using the candidate branch lane line, that is, the candidate branch lane line matching the turning driving trajectory can determine at least one waiting area lane. For example, in a wider intersection area, there are parallel waiting area lanes, and in a narrower intersection area, there is only a single waiting area lane.

[0063] The road structure information of the waiting area is generated according to the at least one target waiting area. After determining the at least one target waiting area, the road structure information of the waiting area is obtained by extracting information from the at least one target waiting area. The road structure information of the waiting area may include only the road structure information of the waiting area corresponding to the road where the vehicle is located, or may include all the road structure information of the waiting area parallel to the waiting area road corresponding to the road where the vehicle is located.

[0064] In an optional embodiment, in step S124, the lane lines in the waiting area are screened based on the historical vehicle driving trajectory, and the candidate branch lane lines include: Step S1241, using a preset direction condition to perform direction screening on the lane lines in the waiting area to be traveled, and obtain a direction screening result, wherein the preset direction condition is used to screen out the lane lines in the waiting area that are consistent with the direction of the historical vehicle driving trajectory; Step S1242, using the second position condition to perform position screening on the direction screening result to obtain candidate branch lane lines, wherein the second position condition is used to screen out lane lines in the waiting area that match the historical vehicle driving trajectory position.

[0065] Specifically, the preset direction condition is used to perform direction screening on the lane lines in the waiting area, and the lane lines in the waiting area that are inconsistent with the direction of the historical vehicle driving trajectory are filtered out, and the lane lines in the waiting area that are consistent with the direction of the historical vehicle driving trajectory are retained as the direction screening results. Further, the second position condition is used to perform position screening on the direction screening results, and the lane lines in the waiting area that are closest to the historical vehicle driving trajectory in a geometric sense, that is, the lane lines in the waiting area that meet the second position condition, are retained, so as to be determined as candidate branch lane lines.

[0066] Based on the above optional embodiments, the lane lines in the waiting area are directionally screened using preset direction conditions to obtain direction screening results, and then the direction screening results are positionally screened using the second position conditions to obtain candidate branch lane lines. Through the dual screening of direction and position, accurate matching of candidate branch lane lines is achieved, which not only improves the decision-making reliability of autonomous driving vehicles when driving at intersections, but also ensures driving safety and efficiency, while optimizing the driving experience.

[0067] Based on the above optional embodiments, by screening and processing the historical vehicle uploaded data, the first stop line and the crosswalk area can be accurately identified and located, and then the lane line layout within the preset range near the first stop line is deeply analyzed to accurately obtain the lane line search results and the stop line search results. Then, the lane line of the waiting area is screened and processed based on the lane line search results and the stop line search results to obtain the lane line of the waiting area. The lane line of the waiting area is screened and processed based on the historical vehicle driving trajectory to obtain the candidate branch lane line. Then, the candidate branch lane line is used to determine at least one target waiting area. Finally, the road structure information of the waiting area is generated based on at least one target waiting area. It can effectively overcome the problems of insufficient coverage of high-precision maps and real-time perception limitations, and provide robust and reliable road information support for autonomous driving technology in practical applications, especially in driving decisions at intersections in the waiting area. It provides higher accuracy and flexibility, greatly enhancing the intelligence and safety of vehicles when passing through intersections.

[0068] In an optional embodiment, in step S123, the lane lines in the waiting area are obtained by filtering and processing according to the lane line search results and the stop line search results, including: Step S1231, determining a second stop line based on the first stop line associated with the stop line search result; Step S1232, in response to the second stop line and the lane line search result satisfying the first position condition, performing association processing on the second stop line and the lane line search result to obtain an association pairing result, wherein the first position condition is used to represent an association adsorption condition between the second stop line and the lane line search result; Step S1233: construct lane lines in the waiting area using the association pairing results.

[0069] Specifically, a second stop line ahead of the first stop line is searched according to the navigation direction, and the second stop line is associated and adsorbed with the lane line search results. Figure 5 is a schematic diagram of an associated adsorption process according to one embodiment of the present disclosure, such as Figure 5 As shown in the figure, when there is a point in the lane line search result whose projection length onto the second stop line is less than 2.5m, it is determined that the second stop line and the lane line search result meet the associated adsorption condition, the second stop line and the lane line search result can be successfully adsorbed, and the adsorption point between the two is on the second stop line or its extension line, thereby obtaining an associated pairing result. When there is no point in the lane line search result whose projection length onto the second stop line is less than 2.5m, it is determined that the second stop line and the lane line search result do not meet the associated adsorption condition, the second stop line and the lane line search result fail to be adsorbed, and the lane line search result will be discarded. The associated pairing result can be used to construct Figure 4 The lane line of the waiting area is marked by the middle circle.

[0070] Based on the above optional embodiment, the second stop line is determined based on the first stop line associated with the stop line search result, and then in response to the second stop line and the lane line search result satisfying the first position condition, the second stop line and the lane line search result are associated to obtain an associated pairing result, and finally the associated pairing result is used to construct the lane line of the waiting area, thereby significantly improving the positioning accuracy, decision reliability and driving efficiency of the autonomous driving vehicle when driving at an intersection.

[0071] In an optional embodiment, the road structure information of the waiting area includes: a first intersection position and a center line of the waiting area, wherein the first intersection position is used to indicate the intersection position of the historical vehicle driving trajectory and the second stop line, and the center line of the waiting area is used to indicate the center line of the lane corresponding to the target waiting area.

[0072] Specifically, the first intersection position can mark the exact location where the historical vehicle left the target waiting area, providing the target vehicle with a clear coordinate of the end point of the driving path, which helps the target vehicle determine when and from which point to leave the target waiting area. The first intersection position can be used as an important basis for the autonomous driving system to make decisions on turning, going straight or stopping, ensuring that the target vehicle can accurately perform driving actions in accordance with traffic regulations when passing through intersections, avoiding violations such as running red lights or wrong turns. The first intersection position can also be used to predict the action paths of other vehicles or pedestrians, which helps to identify potential traffic conflict points in advance, provide safety warnings for autonomous driving vehicles, and ensure driving safety.

[0073] The centerline of the waiting area is a virtual lane line in the target waiting area, which can indicate the optimal driving path of the target vehicle in the target waiting area, helping the target vehicle to stay in the center of the lane and avoid deviation or collision. The centerline of the waiting area is crucial to determining the turning point. The autonomous driving vehicle can judge when to start turning based on its relative position to the centerline to ensure a smooth and safe turning process. The centerline of the waiting area can also be used as a reference line for the target vehicle to maintain a safe distance from the vehicle in front, as well as a basis for speed adjustment, especially in high-density traffic, to ensure that the vehicle passes through intersections safely and efficiently. The centerline of the waiting area is an important input to the vehicle path planning algorithm, which can help the system predict the driving trajectory of the target vehicle in the target waiting area and perform dynamic path planning to adapt to real-time traffic conditions.

[0074] Based on the above optional embodiments, combined with the first intersection position in the local coordinate system and the center line of the waiting area, the autonomous driving vehicle can more accurately locate its position at the intersection, understand the layout and traffic rules of the intersection, and thus make safer, more efficient and compliant driving decisions.

[0075] In an optional embodiment, the road structure information of the waiting area also includes: a second intersection position, a target angle and a target distance, wherein the second intersection position is used to indicate the intersection position of the historical vehicle driving trajectory and the first stop line, the target angle is used to indicate the angle between the first normal direction of the first stop line and the second normal direction of the second stop line, and the target distance is used to indicate the distance between the first intersection position and the second intersection position.

[0076] Optionally, the first stop line and the second stop line may also be parallel to each other. In this case, the target angle is 0°.

[0077] The second intersection position can help the autonomous driving system adjust the vehicle status in advance, such as speed adjustment, steering prediction, etc., to ensure that the vehicle smoothly enters the target waiting area. The second intersection position is used as a reference point for path planning to ensure that the autonomous driving vehicle can accurately align with the entrance of the waiting area and avoid deviating from the correct driving route in complex traffic environments.

[0078] The target angle provides quantitative information about the change in direction between the first stop line and the second stop line. For autonomous vehicles, the target angle is the key basis for adjusting the driving direction, ensuring that the vehicle can correctly align with the exit direction when driving in the waiting area. The size of the target angle can reflect the complexity of the intersection. A larger angle means that the target vehicle needs to make a larger turn, increasing the potential conflict points with other road users. Therefore, it can be used to assess the risk of passing through the intersection and assist the vehicle in making safer driving decisions.

[0079] The target distance is the distance from the first intersection to the second intersection, which is crucial for the autonomous vehicle to estimate the length of the driving path and the time to reach the next key point, and helps the vehicle to prepare for acceleration or deceleration in advance. The target distance can also help the target vehicle determine the safe distance to maintain from the vehicle in front, especially in high-density traffic scenarios. The target vehicle can adjust its speed according to the target distance to avoid rear-end or collision accidents caused by improper distance judgment.

[0080] Based on the above optional embodiments, the second intersection position, target angle and target distance supplement the structural characteristics of the target waiting area, and provide the autonomous driving vehicle with the precise navigation information required to enter, pass and leave the waiting area, which not only helps the vehicle to achieve smoother and safer driving, but also improves the efficiency of passing intersections and reduces driving errors caused by misunderstanding of road structure, thereby optimizing the entire driving experience and ensuring the traffic safety of vehicles and pedestrians.

[0081] Figure 6 is a schematic diagram of road structure information of a waiting area according to one embodiment of the present disclosure, such as Figure 6As shown, the origin of the local coordinate system is the intersection of the first stop line and the leftmost lane line of the intersection, and the coordinate geometry information in the waiting area road structure information is described in the local coordinate system.

[0082] Figure 7 is a schematic diagram of a process for generating a center line of a waiting area according to one embodiment of the present disclosure, such as Figure 7 As shown in the figure, discrete points are sampled at equal intervals on the right lane line of the target waiting area. For each sampling point, the line segment extending to the left in the normal direction intersects with the left lane line of the target waiting area to generate an intersection point. The mean point between the sampling point and the corresponding intersection point is taken as the point on the center line of the waiting area, so as to construct the center line of the waiting area using multiple points. If there is still a certain distance between the center line of the waiting area and the second stop line, it is extended to the second stop line in the direction of the existing center line of the waiting area.

[0083] Before the target vehicle drives to the intersection of the waiting area, it will use the road structure information of the waiting area as a priori, and determine the real-time position of the origin of the local coordinate system in the road structure information of the waiting area in the own vehicle coordinate system through real-time perception, so that the road structure information of the waiting area can be mapped to the own vehicle coordinate system through coordinate transformation. The centerline position information of the waiting area after conversion is directly used and consumed by the vehicle side, and is the key reference information that the vehicle side relies on to build the road topology structure of the waiting area in real time. The vehicle side extends the lane in front of the intersection forward along the centerline of the waiting area until it reaches the end position of the second stop line, and the road structure of the waiting area on the vehicle side is completed. The downstream planning decision only needs to let the own vehicle know the traffic light status at the intersection, judge and drive along the centerline of the waiting area, so as to ensure the driving experience of the own vehicle at the intersection.

[0084] In an optional embodiment, in step S13, sending the road structure information of the waiting area to the target vehicle includes: Based on the received positioning information and navigation route information of the target vehicle, determine whether there is a waiting area road structure at the intersection to be passed within a preset distance from the positioning information on the navigation route; if there is a waiting area road structure at the intersection to be passed, the waiting area road structure information corresponding to the intersection to be passed is sent to the target vehicle.

[0085] Specifically, during the above data distribution process, the target vehicle needs to upload the positioning information and navigation route information to the cloud server at the same time. The positioning information uploaded by the target vehicle can be matched with the navigation route in the cloud server to determine the specific position of the vehicle on the navigation route. The matching process can use the vehicle GPS and the vehicle's driving status information, such as speed and direction, to ensure the accuracy of positioning. Furthermore, it is determined whether there is a waiting area road structure at the intersection to be passed within a preset distance from the positioning information on the navigation route. The setting of the preset distance needs to take into account the driving speed of the target vehicle and the complexity of the intersection to ensure that the target vehicle can receive relevant information in a timely manner and respond.

[0086] The waiting area road structure information previously generated in the cloud server is used to determine whether the intersection to be passed by the target vehicle has a waiting area road structure. If it is determined that the intersection to be passed has a waiting area road structure, the waiting area road structure information will be sent to the target vehicle in a timely manner. This ensures that the target vehicle can obtain the necessary road structure information and operation guide when approaching or arriving at an intersection with a waiting area, which can improve the safety and efficiency of passing the intersection, whether it is processed by the autonomous driving system or referred to by the driver.

[0087] Due to the delay in data transmission, especially when the communication network is unstable or the communication volume is large, by limiting the range of information sent each time to the preset distance, the size of the data packet can be reduced, the information transmission can be accelerated, and the impact of communication delay on the real-time operation of the vehicle can be reduced. This is especially important for autonomous driving vehicles that need to adjust the path in real time, ensuring that the system can obtain and process key information at the intersection ahead in a timely manner and respond quickly.

[0088] In addition, in a dynamically changing traffic environment, road conditions (such as construction, accidents, changes in traffic rules, etc.) may change at any time. By frequently updating the road structure information in the waiting area at a preset distance, the target vehicle can obtain the latest road condition information in a timely manner and adjust the driving strategy to deal with emergencies, thereby enhancing the vehicle's adaptability and safety in complex environments.

[0089] For example, after the target vehicle needs to upload the positioning information and navigation route information to the cloud server at the same time, the cloud server determines whether there is a waiting area road structure at the waiting intersection within 100m from the positioning information on the navigation route. When there is a waiting area road structure at the waiting intersection within 100m from the positioning information on the navigation route, the cloud server can send the waiting area road structure information corresponding to the waiting intersection to the target vehicle. The range of 100m is usually sufficient to cover the waiting intersections that the target vehicle is about to encounter, especially in urban driving environments. By sending the waiting area road structure information 100m in advance, the target vehicle can understand the layout and rules of the complex intersection ahead in advance, so as to make safer and more timely driving decisions.

[0090] In an optional embodiment, in step S13, sending the road structure information of the waiting area to the target vehicle includes: Based on the navigation route information, the road structure information of the waiting area corresponding to the navigation route is obtained; and all the road structure information of the waiting area corresponding to the navigation route is sent to the target vehicle, so that the target vehicle matches the corresponding road structure information of the waiting area based on the positioning information.

[0091] Specifically, in the above data sending process, after the target vehicle needs to upload the navigation route information to the cloud server, the cloud server can parse the navigation route information, thereby identifying all the waiting area intersections that may be involved in the entire route. For example, the cloud server can compare the navigation route with the high-precision map data, identify specific intersection signs and waiting area features, and thus quickly determine the waiting area intersections in the navigation route. Furthermore, the waiting area road structure information corresponding to all the waiting area intersections in the navigation route is obtained, and all the waiting area road structure information corresponding to the navigation route is sent to the target vehicle.

[0092] Unlike the way of sending information in sections, the cloud server chooses to send all the road structure information of the waiting area involved in the entire navigation route to the target vehicle at one time, thereby ensuring that the vehicle has complete key road information during driving, even when communication is limited or interrupted, thereby improving the robustness of the system and the vehicle's autonomous driving capabilities. After receiving the road structure information of the waiting area sent by the cloud, the target vehicle will use its own real-time positioning information to match this information. Through the matching process, the target vehicle can determine when, where, and how to safely pass the waiting area intersection.

[0093] In addition, sending all the road structure information of the waiting area corresponding to the navigation route at one time can also reduce the frequent communication needs between the target vehicle and the cloud server, thereby reducing the impact of communication delays on the driving experience. At the same time, complete road information provides the vehicle with a broader perspective, allowing it to consider more factors when planning the route, such as avoiding congestion and optimizing turning timing, thereby achieving smoother and more efficient driving. In some areas with poor communication, such as tunnels, under viaducts or in remote areas, the communication between the target vehicle and the cloud server may be unstable or completely interrupted. Obtaining all the road structure information of the waiting area at one time allows the target vehicle to make reasonable driving decisions based on the road structure information of the waiting area in the vehicle even when communication is limited, avoiding information loss caused by communication problems, thereby ensuring driving safety and efficiency.

[0094] In an optional embodiment, in step S13, sending the road structure information of the waiting area to the target vehicle includes: Based on the navigation route information, the road structure information of the waiting area corresponding to the navigation route is obtained; based on the positioning information, the road structure information of the waiting area corresponding to the navigation route is periodically sent to the target vehicle according to a preset number, so that the target vehicle matches the corresponding road structure information of the waiting area based on the positioning information.

[0095] Specifically, in the above data sending process, after the target vehicle needs to upload the navigation route information to the cloud server, the cloud server first parses the navigation route information uploaded by the target vehicle and identifies all the waiting area intersections involved in the route. Subsequently, the waiting area road structure information of these waiting area intersections is extracted from the cloud server. In order to avoid communication delays and bandwidth occupation that may be caused by transmitting a large amount of data at one time, the cloud server divides the extracted waiting area road structure information into segments according to a preset number, for example, each segment contains the waiting area road structure information of 3 intersections, and then periodically sends the waiting area road structure information of 3 intersections to the target vehicle. It should be noted that the time interval for periodic sending should be determined according to the driving speed and communication environment of the target vehicle to ensure that the target vehicle can receive the relevant waiting area road structure information before approaching the next waiting area.

[0096] After receiving the information sent from the cloud, the target vehicle uses its real-time positioning information to match the segmented waiting area road structure information. The target vehicle can pre-load and process the waiting area information that is about to arrive. When actually passing the intersection, the target vehicle already has complete road semantic information, so that it can make more accurate decisions, providing necessary support for both automatic route planning and assisting the driver in manual driving.

[0097] In addition, the periodic transmission of a preset amount of waiting area road structure information effectively reduces the amount of single data transmission and avoids the communication bottleneck that may be caused by the one-time transmission of a large amount of information. By periodically updating the waiting area road structure information, the target vehicle can obtain the latest road conditions and traffic rules in a timely manner. If there are temporary changes (such as new construction areas, traffic control, etc.), the cloud server can immediately update the information and send it to the vehicle in the next cycle, realizing rapid adjustment of information and dynamic optimization of routes.

[0098] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0099] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present disclosure, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present disclosure.

[0100] Figure 8 is a structural block diagram of a vehicle for constructing a road in a waiting area in a map according to one embodiment of the present disclosure, such as Figure 8 As shown, the vehicle comprises: The sending module 801 is used to send the vehicle's location information and navigation route information to the cloud server; The receiving module 802 is used to receive the road structure information of the waiting area sent by the cloud server, wherein the road structure information of the waiting area is the road structure information of the waiting area of ​​the waiting intersection within a preset distance from the positioning information; The display module 803 is used to display the road structure information of the waiting area on the graphical user interface of the vehicle.

[0101] Fig. 9 is a structural block diagram of another vehicle for constructing a road in a waiting area in a map according to one embodiment of the present disclosure, such as Fig. 9 As shown, the vehicle comprises: The sending module 901 is used to send the navigation route information of the vehicle to the cloud server; The receiving module 902 is used to receive all the road structure information of the waiting area on the navigation route sent by the cloud server; A matching module 903 is used to match corresponding road structure information of the waiting area from all road structure information of the waiting area based on the positioning information of the vehicle, wherein the corresponding road structure information of the waiting area is the road structure information of the waiting area of ​​the waiting intersection within a preset distance from the positioning information; The display module 904 is used to display the road information of the waiting area corresponding to the positioning information on the graphical user interface of the vehicle.

[0102] Fig.10 is a structural block diagram of another vehicle for constructing a road in a waiting area in a map according to one embodiment of the present disclosure, such as Fig.10 As shown, the vehicle comprises: The sending module 1001 is used to send the vehicle's location information and navigation route information to the cloud server; The receiving module 1002 is used to periodically receive a preset number of waiting area road structure information sent by the cloud server, wherein the waiting area road structure information is the waiting area road structure information of the waiting intersection on the navigation route; A matching module 1003 is used to match corresponding road structure information in the waiting area from a preset number of road structure information in the waiting area based on the positioning information of the vehicle, wherein the corresponding road structure information in the waiting area is the road structure information in the waiting area of ​​the waiting intersection within a preset distance from the positioning information; The display module 1004 is used to display the road information of the waiting area corresponding to the positioning information on the graphical user interface of the vehicle.

[0103] Fig.11 is a structural block diagram of another vehicle for constructing a road in a waiting area in a map according to one embodiment of the present disclosure, such as Fig.11 As shown, the vehicle comprises: The acquisition module 1101 is used to acquire the vehicle's positioning information, navigation route information and vehicle historical data in the storage module, wherein the vehicle historical data includes: intersection semantic information and historical driving trajectory of the road in the waiting area; A generating module 1102, for generating road structure information of a waiting area according to intersection semantic information and historical driving trajectories; A matching module 1103 is used to match the corresponding waiting area road structure information based on the positioning information and the navigation route information; The display module 1104 is used to display the road structure information of the waiting area on the graphical user interface of the vehicle.

[0104] The above positioning information can obtain the precise location of the vehicle, including longitude and latitude coordinates, through satellite navigation systems such as GPS or Beidou. The above navigation route information can obtain the predetermined driving route from the vehicle's navigation system, which helps to know the intersection to be passed in advance. The above vehicle history data is the intersection semantic information and historical driving trajectory stored when the vehicle passed the waiting area road before, which can be read from the storage module. The vehicle history data can be the vehicle's own driving record in the past, or it can be shared information from other vehicles, which is not limited by the embodiments of the present application.

[0105] Furthermore, the road structure information of the waiting area is generated according to the intersection semantic information and the historical driving trajectory, so that the corresponding road structure information of the waiting area can be automatically matched according to the positioning information of the vehicle and the navigation route information. In the matching process, periodic batch matching can be performed according to the preset number, or the road structure information of the waiting area of ​​a single waiting intersection can be matched instantly according to the positioning information, and the road structure information of the waiting area of ​​all the waiting intersections on the navigation route can be matched at one time.

[0106] In the embodiment of the present application, when the vehicle directly constructs the road in the waiting area, there is no need to wait for the data from the cloud server to be sent. The vehicle's own sensors and computing resources are used to make real-time judgments and constructions on the surrounding environment, which is particularly suitable for areas with limited communication or unreliable networks. The vehicle-side independently constructs the road structure in the waiting area, avoiding communication delays that may occur during data transmission and ensuring the immediacy of driving decisions. The vehicle can autonomously identify the waiting area and construct the road structure without external information, which is crucial for the safety and reliability of autonomous driving vehicles in complex road environments. The method of directly executing the construction of the road in the waiting area by the target vehicle can be specifically applicable to areas with poor communication conditions, such as remote areas, tunnels or under viaducts, and can also be applied to high-speed lane changes and emergency response. The vehicle-side directly constructs a driving environment that can quickly adapt to changes, and can also be applied to autonomous driving scenarios with high requirements for real-time and autonomy, such as high-level autonomous driving testing or operations.

[0107] Optionally, the intersection semantic information includes: a first stop line, a second stop line, a crosswalk area, and candidate branch lane lines, wherein the first stop line is used to indicate the stop line of the straight lane of the waiting area road, and the second stop line is used to indicate the stop line associated with the candidate branch lane line.

[0108] Optionally, the generation module 1102 also includes: a first screening unit, used to screen and process the vehicle historical data to obtain a first stop line and a crosswalk area; a search unit, used to search and process the lane lines within a preset range near the first stop line based on the first stop line and the crosswalk area, and obtain lane line search results and stop line search results; a second screening unit, used to screen and process the lane lines in the waiting area based on the lane line search results and the stop line search results, and obtain the lane lines in the waiting area; a third screening unit, used to screen and process the lane lines in the waiting area based on the historical driving trajectory, and obtain candidate branch lane lines; a determination unit, used to determine at least one target waiting area using the candidate branch lane lines; a generation unit, used to generate road structure information of the waiting area based on at least one target waiting area.

[0109] Optionally, the second screening unit is also used to: determine the second stop line based on the first stop line associated with the stop line search result; in response to the second stop line and the lane line search result satisfying the first position condition, associate the second stop line with the lane line search result to obtain an associated pairing result, wherein the first position condition is used to represent the associated adsorption condition between the second stop line and the lane line search result; and use the associated pairing result to construct the lane line of the area to be traveled.

[0110] Optionally, the road structure information of the waiting area includes: a first intersection position and a center line of the waiting area, wherein the first intersection position is used to indicate the intersection position of the historical driving trajectory and the second stop line, and the center line of the waiting area is used to indicate the center line of the lane corresponding to the target waiting area.

[0111] Optionally, the road structure information of the waiting area also includes: a second intersection position, a target angle and a target distance, wherein the second intersection position is used to indicate the intersection position of the historical driving trajectory and the first stop line, the target angle is used to indicate the angle between the first normal direction of the first stop line and the second normal direction of the second stop line, and the target distance is used to indicate the distance between the first intersection position and the second intersection position.

[0112] Optionally, the matching module 1103 also includes: a judgment unit, used to judge whether there is a waiting area road structure at the intersection to be passed within a preset distance from the positioning information on the navigation route based on the positioning information and the navigation route information; a first matching unit, used to obtain the waiting area road structure information corresponding to the intersection to be passed based on the positioning information when there is a waiting area road structure at the intersection to be passed.

[0113] Optionally, the matching module 1103 also includes: a first acquisition unit, used to acquire all the road structure information of the waiting area corresponding to the navigation route based on the navigation route information; a second matching unit, used to match the corresponding road structure information of the waiting area from all the road structure information of the waiting area based on the positioning information, wherein the corresponding road structure information of the waiting area is the road structure information of the waiting area of ​​the intersection to be passed within a preset distance from the positioning information.

[0114] Optionally, the matching module 1103 also includes: a second acquisition unit, used to periodically acquire the road structure information of the waiting area corresponding to a preset number of navigation routes based on the navigation route information; a third matching unit, used to match the corresponding road structure information of the waiting area from the road structure information of the waiting area corresponding to a preset number of navigation routes based on the positioning information, wherein the corresponding road structure information of the waiting area is the road structure information of the waiting area of ​​the intersection to be passed within a preset distance from the positioning information.

[0115] Optionally, the waiting area road includes at least one of the following: a left-turn waiting area road, a right-turn waiting area road and a straight-ahead waiting area road.

[0116] It should be noted that the above-mentioned units and modules can be implemented by software or hardware. For the latter, it can be implemented in the following ways, but not limited to this: the above-mentioned units and modules are all located in the same processor; or, the above-mentioned units and modules are located in different processors in any combination.

[0117] An embodiment of the present disclosure further provides a cloud server, comprising: a memory storing an executable program; and a processor for running the program, wherein the method in each embodiment of the present disclosure is executed when the program is running.

[0118] An embodiment of the present disclosure further provides a computer-readable storage medium, which includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present disclosure.

[0119] The embodiments of the present disclosure further provide a computer program product, including a computer program, which implements the methods in the various embodiments of the present disclosure when executed by a processor.

[0120] An embodiment of the present disclosure further provides a computer program product, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present disclosure is implemented.

[0121] The embodiments of the present disclosure further provide a computer program, which implements the methods in the above-mentioned embodiments of the present disclosure when executed by a processor.

[0122] The serial numbers of the above-mentioned embodiments of the present disclosure are only for description and do not represent the advantages or disadvantages of the embodiments.

[0123] In the above embodiments of the present disclosure, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0124] In the several embodiments provided in the present disclosure, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0125] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0126] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0127] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present disclosure, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present disclosure. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc. Various media that can store program codes.

[0128] The above is only a preferred embodiment of the present disclosure. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present disclosure. These improvements and modifications should also be regarded as the scope of protection of the present disclosure.

Claims

1. A method for constructing a road in a waiting area in a map, characterized in that: include: Acquire historical vehicle upload data, wherein the historical vehicle upload data includes: intersection semantic information of waiting area roads uploaded by historical vehicles and historical vehicle driving tracks; Generate road structure information of the waiting area according to the intersection semantic information and the historical vehicle driving trajectory; In response to receiving the positioning information and / or navigation route information reported by the target vehicle, the road structure information of the waiting area is sent to the target vehicle, so that the target vehicle displays the road structure information of the waiting area.

2. The method according to claim 1, characterized in that The intersection semantic information includes: a first stop line, a second stop line, a crosswalk area, and candidate branch lane lines, wherein the first stop line is used to represent the stop line of the straight lane of the waiting area road, and the second stop line is used to represent the stop line associated with the candidate branch lane line.

3. The method according to claim 2, characterized in that Generating the road structure information of the waiting area according to the intersection semantic information and the historical vehicle driving trajectory includes: Screening and processing the historical vehicle uploaded data to obtain the first stop line and the pedestrian crossing area; Based on the first stop line and the crosswalk area, a lane line within a preset range near the first stop line is searched and processed to obtain a lane line search result and a stop line search result; Perform screening processing according to the lane line search results and the stop line search results to obtain the lane lines of the waiting area; Based on the historical vehicle driving trajectory, the lane lines in the waiting area are screened to obtain the candidate branch lane lines; Determine at least one target waiting area using the candidate branch lane line; The road structure information of the waiting area is generated according to the at least one target waiting area.

4. The method according to claim 3, characterized in that The lane lines of the waiting area are obtained by filtering and processing according to the lane line search results and the stop line search results, including: determining the second stop line based on the first stop line associated with the stop line search result; In response to the second stop line and the lane line search result satisfying a first position condition, performing association processing on the second stop line and the lane line search result to obtain an association pairing result, wherein the first position condition is used to represent an association adsorption condition between the second stop line and the lane line search result; The lane line of the waiting area is constructed using the association pairing result.

5. The method according to claim 3, characterized in that: The road structure information of the waiting area includes: a first intersection position and a center line of the waiting area, wherein the first intersection position is used to represent the intersection position of the historical vehicle driving trajectory and the second stop line, and the center line of the waiting area is used to represent the center line of the lane corresponding to the target waiting area.

6. The method according to claim 5, characterized in that The road structure information of the waiting area also includes: a second intersection position, a target angle and a target distance, wherein the second intersection position is used to indicate the intersection position of the historical vehicle driving trajectory and the first stop line, the target angle is used to indicate the angle between the first normal direction of the first stop line and the second normal direction of the second stop line, and the target distance is used to indicate the distance between the first intersection position and the second intersection position.

7. The method according to claim 1, characterized in that Sending the road structure information of the waiting area to the target vehicle includes: According to the received positioning information of the target vehicle and the navigation route information, determining whether there is a waiting area road structure at a waiting intersection within a preset distance from the positioning information on the navigation route; If the road structure in the waiting area exists at the intersection to be passed, the road structure information in the waiting area corresponding to the intersection to be passed is sent to the target vehicle.

8. The method according to claim 1, characterized in that Sending the road structure information of the waiting area to the target vehicle includes: Acquiring the road structure information of the waiting area corresponding to the navigation route based on the navigation route information; All the road structure information of the waiting area corresponding to the navigation route is sent to the target vehicle, so that the target vehicle matches the corresponding road structure information of the waiting area based on the positioning information.

9. The method according to claim 1, characterized in that: Sending the road structure information of the waiting area to the target vehicle includes: Acquiring the road structure information of the waiting area corresponding to the navigation route based on the navigation route information; According to the positioning information, the road structure information of the waiting area corresponding to the navigation route is periodically sent to the target vehicle according to a preset number, so that the target vehicle matches the corresponding road structure information of the waiting area based on the positioning information.

10. The method according to claim 1, characterized in that The waiting area road includes at least one of the following: a left-turn waiting area road, a right-turn waiting area road and a straight-ahead waiting area road.

11. A vehicle for constructing a waiting area road in a map, characterized in that: include: A sending module is used to send the vehicle's location information and navigation route information to the cloud server; A receiving module, used for receiving the road structure information of the waiting area sent by the cloud server, wherein the road structure information of the waiting area is the road structure information of the waiting area of ​​the waiting intersection within a preset distance from the positioning information; A display module is used to display the road structure information of the waiting area on the graphical user interface of the vehicle.

12. A vehicle for constructing a waiting area road in a map, characterized in that: include: A sending module, used to send the navigation route information of the vehicle to the cloud server; A receiving module, used for receiving all the road structure information of the waiting area on the navigation route sent by the cloud server; A matching module, configured to match the corresponding road structure information of the waiting area from all the road structure information of the waiting area based on the positioning information of the vehicle, wherein the corresponding road structure information of the waiting area is the road structure information of the waiting area of ​​the waiting intersection within a preset distance from the positioning information; A display module is used to display the road information of the waiting area corresponding to the positioning information on the graphical user interface of the vehicle.

13. A vehicle for constructing a waiting area road in a map, characterized in that: include: A sending module is used to send the vehicle's location information and navigation route information to the cloud server; A receiving module, used for periodically receiving a preset number of waiting area road structure information sent by the cloud server, wherein the waiting area road structure information is the waiting area road structure information of the waiting intersection on the navigation route; A matching module, configured to match the corresponding road structure information of the waiting area from the preset number of road structure information of the waiting area based on the positioning information of the vehicle, wherein the corresponding road structure information of the waiting area is the road structure information of the waiting area of ​​the waiting intersection within a preset distance from the positioning information; A display module is used to display the road information of the waiting area corresponding to the positioning information on the graphical user interface of the vehicle.

14. A vehicle for constructing a waiting area road in a map, characterized in that: include: An acquisition module, used to acquire the vehicle's positioning information, navigation route information and vehicle historical data in the storage module, wherein the vehicle historical data includes: intersection semantic information and historical driving trajectory of the road in the waiting area; A generating module, used for generating road structure information of a waiting area according to the intersection semantic information and the historical driving trajectory; A matching module, used for matching the corresponding road structure information of the waiting area based on the positioning information and the navigation route information; A display module is used to display the road structure information of the waiting area on the graphical user interface of the vehicle.

15. The vehicle according to claim 14, characterized in that The intersection semantic information includes: a first stop line, a second stop line, a crosswalk area, and candidate branch lane lines, wherein the first stop line is used to represent the stop line of the straight lane of the waiting area road, and the second stop line is used to represent the stop line associated with the candidate branch lane line.

16. The vehicle according to claim 15, characterized in that The generating module also includes: A first screening unit, configured to screen the vehicle history data to obtain the first stop line and the crosswalk area; A search unit, configured to search for lane lines within a preset range near the first stop line based on the first stop line and the crosswalk area, and obtain a lane line search result and a stop line search result; A second screening unit is used to perform screening processing according to the lane line search result and the stop line search result to obtain the lane line of the waiting area; A third screening unit, configured to screen the lane lines in the waiting area based on the historical driving trajectory to obtain the candidate branch lane lines; A determination unit, configured to determine at least one target waiting area using the candidate branch lane line; A generating unit is used to generate the road structure information of the waiting area according to the at least one target waiting area.

17. The vehicle according to claim 16, characterized in that The second screening unit is also used for: determining the second stop line based on the first stop line associated with the stop line search result; In response to the second stop line and the lane line search result satisfying a first position condition, performing association processing on the second stop line and the lane line search result to obtain an association pairing result, wherein the first position condition is used to represent an association adsorption condition between the second stop line and the lane line search result; The lane line of the waiting area is constructed using the association pairing result.

18. The vehicle according to claim 16, characterized in that The road structure information of the waiting area includes: a first intersection position and a center line of the waiting area, wherein the first intersection position is used to indicate the intersection position of the historical driving trajectory and the second stop line, and the center line of the waiting area is used to indicate the center line of the lane corresponding to the target waiting area.

19. The vehicle according to claim 18, characterized in that The road structure information of the waiting area also includes: a second intersection position, a target angle and a target distance, wherein the second intersection position is used to indicate the intersection position of the historical driving trajectory and the first stop line, the target angle is used to indicate the angle between the first normal direction of the first stop line and the second normal direction of the second stop line, and the target distance is used to indicate the distance between the first intersection position and the second intersection position.

20. The vehicle of claim 14, wherein: The matching module also includes: A judgment unit, configured to judge whether there is a waiting area road structure at a waiting intersection within a preset distance from the positioning information on the navigation route according to the positioning information and the navigation route information; The first matching unit is used for obtaining the road structure information of the waiting area corresponding to the intersection to be passed based on the positioning information when the road structure of the waiting area exists at the intersection to be passed.

21. The vehicle according to claim 14, characterized in that The matching module also includes: A first acquisition unit, configured to acquire all road structure information of the waiting area corresponding to the navigation route based on the navigation route information; A second matching unit is used to match the corresponding road structure information of the waiting area from all the road structure information of the waiting area based on the positioning information, wherein the corresponding road structure information of the waiting area is the road structure information of the waiting area of ​​the waiting intersection within a preset distance from the positioning information.

22. The vehicle according to claim 14, characterized in that The matching module also includes: A second acquisition unit, configured to periodically acquire the road structure information of the waiting area corresponding to a preset number of navigation routes based on the navigation route information; A third matching unit is used to match the corresponding road structure information in the waiting area from the road structure information in the waiting area corresponding to a preset number of navigation routes based on the positioning information, wherein the corresponding road structure information in the waiting area is the road structure information in the waiting area of ​​the intersection to be passed within a preset distance from the positioning information.

23. The vehicle according to claim 14, characterized in that The waiting area road includes one of the following: a left-turn waiting area road, a right-turn waiting area road and a straight-ahead waiting area road.

24. A cloud server, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the method for constructing a road in a waiting area in a map as described in any one of claims 1 to 10.

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