Vehicle guiding information generation method and electronic equipment

Abstract

The invention provides a vehicle guiding information generation method and electronic equipment, and the method comprises the steps: determining a passable region of a target vehicle according to a target road under the condition that the vehicle driving information of the target vehicle and the road information of the target road are received, the vehicle driving information is information generated in the driving process of the target vehicle on the target road; determining to-be-adjusted vehicle guiding information of the target vehicle according to the vehicle driving information and the passable area; determining an obstacle corresponding to the target vehicle according to the road information, and adjusting the to-be-adjusted vehicle guiding information according to the obstacle to obtain target vehicle guiding information; and sending the target vehicle guiding information to the target vehicle, so that a driver of the target vehicle controls the target vehicle to run based on the target vehicle guiding information. According to the invention, accurate target vehicle guiding information can be obtained.

Description

Technical Field

[0001] This disclosure relates to the field of driver assistance technology, and in particular to a method and apparatus for generating vehicle guidance information, electronic equipment, computer-readable storage medium, and computer program product. Background Technology

[0002] With the continuous development of computer technology and driver assistance technology, vehicle guidance information can be provided to vehicles during driving, thereby assisting the vehicle in driving.

[0003] In the process of determining vehicle guidance information, the related technologies often produce inaccurate information due to insufficient road information and the inability to handle obstacles. Therefore, how to accurately generate vehicle guidance information has become an urgent problem to be solved. Summary of the Invention

[0004] This disclosure provides a method and apparatus for generating vehicle guidance information, an electronic device, a computer-readable storage medium, and a computer program product.

[0005] In a first aspect, this disclosure provides a method for generating vehicle guidance information. The method includes: upon receiving vehicle driving information of a target vehicle and road information of a target road, determining a passable area for the target vehicle based on the target road, wherein the vehicle driving information is information generated during the target vehicle's travel on the target road; determining vehicle guidance information to be adjusted for the target vehicle based on the vehicle driving information and the passable area; determining obstacles corresponding to the target vehicle based on the road information, and adjusting the vehicle guidance information to be adjusted based on the obstacles to obtain target vehicle guidance information; and sending the target vehicle guidance information to the target vehicle so that the driver of the target vehicle can control the target vehicle to drive based on the target vehicle guidance information.

[0006] Secondly, this disclosure provides a vehicle guidance information generation device, which includes: a region determination module, a first information determination module, a second information determination module, and an information sending module.

[0007] The area determination module is used to determine the passable area of ​​the target vehicle based on the target road when it receives the vehicle driving information of the target vehicle and the road information of the target road. The vehicle driving information is the information generated by the target vehicle during its travel on the target road.

[0008] The first information determination module is used to determine the vehicle guidance information to be adjusted for the target vehicle based on the vehicle driving information and the passable area.

[0009] The second information determination module is used to determine the obstacles corresponding to the target vehicle based on the road information, and adjust the vehicle guidance information to be adjusted based on the obstacles to obtain the target vehicle guidance information.

[0010] The information sending module is used to send the target vehicle guidance information to the target vehicle so that the driver of the target vehicle can control the target vehicle to drive based on the target vehicle guidance information.

[0011] Thirdly, this disclosure provides an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores one or more computer programs executable by the at least one processor, the one or more computer programs being executed by the at least one processor to enable the at least one processor to perform the vehicle guidance information generation method described above.

[0012] Fourthly, this disclosure provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the above-described vehicle guidance information generation method.

[0013] Fifthly, this disclosure provides a computer program product comprising computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code, wherein when the computer-readable code is executed in a processor of an electronic device, the processor in the electronic device performs the vehicle guidance information generation method described above.

[0014] The vehicle guidance information generation method provided in this disclosure can receive various information data, such as the vehicle driving information of the target vehicle and the road information of the target road, thus avoiding the problem of insufficient data in the process of generating vehicle guidance information. Furthermore, in the process of generating target vehicle guidance information, the method first determines the passable area of ​​the target vehicle based on the target road, and then determines the accurate vehicle guidance information to be adjusted for the target vehicle based on the vehicle driving information and the passable area. Considering the complexity of road conditions, there may be obstacles affecting vehicle driving. This method can determine the obstacles corresponding to the target vehicle based on the road information and adjust the vehicle guidance information to be adjusted based on the obstacles to obtain more accurate target vehicle guidance information. Then, the target vehicle guidance information is sent to the target vehicle, enabling the driver of the target vehicle to control the target vehicle's driving based on the more accurate target vehicle guidance information.

[0015] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0016] The accompanying drawings are provided to further illustrate the present disclosure and form part of the specification. They are used together with the embodiments of the present disclosure to explain the disclosure and do not constitute a limitation thereof. The above and other features and advantages will become more apparent to those skilled in the art from the detailed description of exemplary embodiments with reference to the accompanying drawings, in which:

[0017] Figure 1 This is a flowchart of a vehicle guidance information generation method provided in an embodiment of the present disclosure.

[0018] Figure 2 This is a schematic diagram of data reporting in a vehicle guidance information generation method provided in an embodiment of this disclosure.

[0019] Figure 3 This is a schematic diagram of guide line adjustment in a vehicle guidance information generation method provided in this embodiment of the present disclosure.

[0020] Figure 4 This is a schematic diagram illustrating the processing steps of a vehicle guidance information generation method provided in an embodiment of this disclosure.

[0021] Figure 5 This is a block diagram of a vehicle guidance information generation device provided in an embodiment of the present disclosure.

[0022] Figure 6 This is a block diagram of an electronic device provided in an embodiment of the present disclosure. Detailed Implementation

[0023] To enable those skilled in the art to better understand the technical solutions of this disclosure, exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments of this disclosure to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0024] Where there is no conflict, the various embodiments of this disclosure and the features thereof in the embodiments may be combined with each other.

[0025] As used herein, the term “and / or” includes any and all combinations of one or more related enumerated entries.

[0026] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. As used herein, the singular forms “a” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that when the terms “comprising” and / or “made of” are used in this specification, the presence of the stated feature, integral, step, operation, element, and / or component is specified, but the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof is not excluded. Words such as “connected” or “linked” are not limited to physical or mechanical connections but can include electrical connections, whether direct or indirect.

[0027] Unless otherwise specified, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and this disclosure, and will not be interpreted as having an idealized or overly formal meaning, unless expressly so defined herein.

[0028] The vehicle guidance information generation method according to embodiments of this disclosure can be executed by an electronic device such as a terminal device or a server. The terminal device can be an in-vehicle device, user equipment (UE), mobile device, user terminal, terminal, cellular phone, cordless phone, personal digital assistant (PDA), handheld device, computing device, in-vehicle device, wearable device, etc. The method can be implemented by a processor calling computer-readable program instructions stored in memory. Alternatively, the method can be executed by a server.

[0029] The technical terms used in the embodiments of this disclosure are explained below.

[0030] RSU (Roadside Unit): A communication and sensing device deployed on the side of the road to collect local traffic environment data and communicate with vehicles or the cloud.

[0031] OBU (On-Board Unit): A communication device installed in a vehicle for exchanging data with the RSU, the cloud, or other vehicles.

[0032] V2X (Vehicle-to-Everything): Communication technology between vehicles and all entities (such as other vehicles, infrastructure, pedestrians).

[0033] Cloud-based: Refers to the cloud control platform, which is responsible for receiving data from the field, performing data fusion, route planning, decision control, and distributing the results to the vehicles. The cloud has high computing power and storage capacity, and combined with high-precision maps, it enables detailed planning.

[0034] ADAS (Advanced Driver Assistance Systems): Systems that assist drivers in controlling vehicles through sensors and algorithms.

[0035] High-precision maps: Digital maps with centimeter-level accuracy, including detailed information such as lane lines and traffic signs.

[0036] Guide lines: These are visual aids provided while driving to help the driver keep the vehicle centered in the lane or on the road for safe driving. Guide lines are usually displayed on the vehicle's dashboard or head-up display and are presented in the form of images or lines.

[0037] Dynamic guide lines: Guide lines whose attributes such as shape, color, or width can be dynamically adjusted in real time, used to visualize risk information.

[0038] AR-HUD stands for Augmented Reality Head-up Display. It overlays virtual information onto the windshield, projecting it onto the real driving scene to enhance driving safety and experience.

[0039] With the continuous development of computer technology and driver assistance technology, vehicle guidance information can be provided to vehicles during operation, thereby assisting vehicle driving. However, due to insufficient road information and the inability to handle obstacles, the generated vehicle guidance information is often inaccurate. Therefore, how to accurately generate vehicle guidance information has become an urgent problem to be solved.

[0040] For example, to address the aforementioned issues, the in-vehicle systems of related technologies mainly employ the following technical solutions for displaying driving routes and environmental risks, but all of them have significant shortcomings.

[0041] The first technical solution is: traditional static navigation system.

[0042] Such systems (like typical in-vehicle navigation maps) plan routes based on map data, generating a static guide line. This guide line only reflects macro-level route selection (e.g., "turn right at the next intersection"), and is completely unable to perceive or respond to dynamic, random obstacles on the road (e.g., temporary construction zones, illegally parked vehicles, non-motorized vehicles crossing the road). Its technical essence is solving the problem of "which road to take," rather than the problem of "how to safely avoid obstacles on the current road."

[0043] The second technical solution is: ADAS display system based on vehicle sensors.

[0044] Advanced driver assistance systems (such as Autopilot visualization in new energy vehicles) perceive the vehicle's surroundings through sensors like cameras and radar, rendering perceived obstacles on the screen as virtual icons (such as vehicle and pedestrian models). However, the navigation guide lines and obstacle perception are displayed on two separate layers. The navigation guide lines (usually solid blue lines) maintain their original path, while perceived obstacles (such as construction vehicles ahead) are displayed as independent icons, possibly with color warnings. The guide lines themselves do not dynamically adjust their shape or path based on obstacles, requiring the driver to manually integrate information and determine whether there is an impact, increasing cognitive load and decision-making time.

[0045] The third technical solution is: a prompting system based on V2X communication.

[0046] Some cutting-edge solutions utilize vehicle-to-everything (V2X) technology, where roadside units (RSUs) perceive traffic events or other vehicles perceive them, and then transmit the event information to the in-vehicle terminal. The vehicle then marks the event location on the navigation interface with additional, static icons (such as warning triangles or construction signs). While this solution provides beyond-line-of-sight perception capabilities, its display is disconnected from navigation guidelines, achieving only "risk marking" rather than "route guidance." It informs the driver "there is danger here," but does not provide intuitive visual guidance on "whether there is an impact and how to pass safely."

[0047] Based on the above, it can be seen that the technical solutions of the relevant technologies have the following defects.

[0048] 1. Perception blind spots and incomplete data: Vehicle sensors are affected by factors such as weather and obstruction, and cannot fully cover the road environment, especially in complex scenarios such as intersections or curves, where perception blind spots exist.

[0049] 2. Fragmented display method: Dynamic obstacle information is usually displayed as an independent icon or text warning, separated from the navigation guide line. Drivers need to use extra mental effort to integrate the information to understand the relationship between the risk location and the driving space, which increases the cognitive load.

[0050] 3. Lack of proactive guidance: Existing systems mostly rely on passive alarms and cannot dynamically adjust path guidance based on obstacles, resulting in insufficient reaction time for drivers in emergency situations and easily leading to safety accidents.

[0051] These shortcomings stem from the fact that the relevant technologies do not deeply integrate dynamic environmental data into the path generation process, and the display design does not consider the intuitiveness of human-computer interaction.

[0052] Based on this, the present disclosure provides a method and apparatus for generating vehicle guidance information, an electronic device, a computer-readable storage medium, and a computer program product, as detailed in the following embodiments.

[0053] Figure 1 A flowchart illustrating a vehicle guidance information generation method provided in this disclosure embodiment. (Refer to...) Figure 1 The method includes steps S11-S14.

[0054] Step S11: Upon receiving the vehicle driving information of the target vehicle and the road information of the target road, determine the passable area of ​​the target vehicle based on the target road, wherein the vehicle driving information is information generated by the target vehicle during its travel on the target road.

[0055] In some embodiments, the vehicle guidance information generation method provided in this disclosure can be applied to the cloud; the cloud can receive the vehicle driving information of the target vehicle and the road information of the target road, and after generating the target vehicle guidance information, send the target vehicle guidance information to the target vehicle.

[0056] The vehicle's driving information includes, but is not limited to, one or more of the following: longitude, latitude, speed, heading angle, acceleration, and deceleration.

[0057] Road information can be understood as the information obtained by detecting a target road. This road information includes, but is not limited to, obstacle information and traffic flow information of the target road; this road information can be information collected by RSU (Roadside Unit).

[0058] The passable area can be understood as an area in the target road that the target vehicle can pass through. For example, the passable area can be a lane or parking space in the target road.

[0059] In some embodiments, receiving the vehicle driving information of the target vehicle and the road information of the target road includes: receiving the vehicle driving information sent by the target vehicle and receiving the road information of the target lane sent by the roadside unit; or, when the target vehicle sends the vehicle driving information to the roadside unit, receiving the vehicle driving information and the road information of the target lane sent by the roadside unit; wherein the vehicle driving information is information collected by the target vehicle through onboard sensors, and the road information is information collected by the roadside unit through configured sensors.

[0060] Specifically, the target vehicle in this disclosure will report its current driving information to the cloud; the roadside unit can also report the road information collected by its own sensors to the cloud. Alternatively, the roadside unit can not only collect road information from its own sensors, but also receive driving information reported by passing vehicles, and report both the road information and the driving information to the cloud for processing.

[0061] Taking the application of the vehicle guidance information generation method provided in this disclosure in the scenario of generating dynamic guide lines as an example, this method for generating vehicle guidance information is explained. Figure 2 This is a schematic diagram of data reporting in a vehicle guidance information generation method provided in this embodiment of the disclosure, based on... Figure 2 As can be seen, the data reporting operation in this method is divided into vehicle-side perception data stream and roadside perception data stream.

[0062] The operations performed by the vehicle-side perception data stream include: data collection and data reporting.

[0063] Data collection: The vehicle (i.e. the target vehicle) collects and fuses data through its own sensors (such as vehicle-mounted cameras, vehicle-mounted radar, millimeter-wave radar) to identify surrounding traffic participants (vehicles, pedestrians, non-motorized vehicles) and events (such as congestion, breakdowns) in real time.

[0064] Data reporting: Vehicles send perceived local event information to the roadside unit (RSU) via V2X communication, or directly report the perceived local event information to the cloud processing center via vehicle-to-cloud communication protocols (such as 4G / 5G). The perceived local event information includes: the vehicle's current position and pose information (including longitude, latitude, speed, heading angle, acceleration, deceleration, etc.) and lane-level navigation information.

[0065] The operations performed by the roadside sensing data stream include: data collection, data fusion, and reporting.

[0066] Data Acquisition: Roadside Units (RSUs) deployed on key road sections (such as intersections and ramps) and their equipped sensors (roadside cameras and roadside radars) provide wide-area, blind-spot-free perception of the coverage area, thereby enabling real-time identification of traffic participants and events.

[0067] Data Fusion and Reporting: Roadside units not only collect data from their own sensors but also receive information reported by passing vehicles via V2X. Through multi-source data fusion and cross-validation, roadside units can improve the confidence of individual source data, filter out false alarms, and ultimately report the validated, high-quality perception results to the cloud; these high-quality perception results include information on traffic participants and events.

[0068] After executing the vehicle-side perception data stream and the roadside perception data stream, the cloud in this method can perform cloud-based decision-making and data stream distribution operations, specifically including the following:

[0069] First, data aggregation: The cloud platform aggregates perception data from various roadside units and a large number of vehicles, performs spatial filtering and data fusion on this data, and thus forms a global, real-time road situation map. This road situation map is a map that represents the traffic conditions of the current target road. Based on this road situation map, information such as the number of pedestrians, the number of vehicles, vehicle speed, and obstacles on the current target road can be determined.

[0070] Safe passage corridor reconstruction: The cloud is equipped with high-precision maps and traffic rules. The high-precision map defines a basic "drivable area." The cloud uses dynamically perceived events (such as obstacle position and size) as constraints, combined with traffic rules (such as solid lines cannot be crossed), to reconstruct a local, safe "dynamic drivable corridor" (such as a drivable area) in real time within the basic drivable area. This corridor defines the virtual spatial boundary where vehicles can safely travel in the next time period.

[0071] Guideline Generation and Distribution: Within the generated "dynamically accessible corridor," the cloud utilizes a path planning algorithm (such as an optimization algorithm considering comfort and efficiency) to generate an optimal dynamic guideline (i.e., target vehicle guidance information). This guideline is distributed to the vehicle (i.e., the target vehicle) via a low-latency communication network. This path planning algorithm can be understood as a dynamic guideline algorithm, used to generate an optimal dynamic guideline.

[0072] Based on the above embodiments, this disclosure addresses the issue of integrating obstacle (such as temporary construction, illegally parked vehicles, and non-motorized vehicle crossing) information sources and overcoming perception blind spots. It provides a multi-source data fusion strategy: through vehicle-road-cloud collaboration, it integrates data from RSU, OBU, and the cloud, overcoming the limitations of a single sensor and achieving high-confidence event perception. Furthermore, it is compatible with situations where there is no perception data source. Because roadside equipment is only deployed in key locations, there may be sections without roadside perception during the entire journey, and the perception capabilities of the vehicle are also limited. Therefore, decoupling is implemented, allowing the dynamic guide lines to still provide normal driving and lane-changing assistance functions without relying on perception.

[0073] Step S12: Determine the vehicle guidance information to be adjusted for the target vehicle based on the vehicle driving information and the passable area.

[0074] Among them, the vehicle guidance information to be adjusted can be understood as the vehicle guidance information that needs to be adjusted.

[0075] The vehicle guidance information can be understood as information that can guide the driver to control the driving of the target vehicle. This vehicle guidance information includes, but is not limited to, guide lines, dynamic guide lines, prompt voice, vibration prompt information, and three-dimensional prompt data.

[0076] The prompt voice can be understood as voice information that guides the driver to control the direction of the target vehicle, such as "Please turn left" or "Please go straight".

[0077] Vibration alert information can be understood as information that guides the driver to control the target vehicle by controlling the vibration of the vehicle's vibration module. The vehicle vibration module can be a device that is installed in the target vehicle and can vibrate, such as a vibration device installed on the steering wheel. The driver's hands can feel the vibration of the vehicle vibration module, thereby controlling the vehicle's movement (such as going straight, turning left, etc.).

[0078] Three-dimensional prompt data can be understood as data displayed through a three-dimensional data display device that can guide the driver in controlling the target vehicle's movement. For example, this three-dimensional data display device can be a 3D projector or an AR-HUD.

[0079] In some embodiments, the vehicle driving information includes vehicle location and speed; determining the vehicle guidance information to be adjusted for the target vehicle based on the vehicle driving information and the passable area includes steps one to three.

[0080] Step 1: Calculate the guidance length based on the vehicle speed, and determine the guidance endpoint position according to the direction of travel of the target vehicle, the guidance length, and the vehicle position. The guidance length is used to represent the length of the lane guided by the vehicle guidance information.

[0081] Specifically, the cloud platform used in the vehicle guidance information generation method provided in this disclosure can receive the current position and pose information (including longitude, latitude, speed, heading angle, acceleration, deceleration, etc.) and lane-level navigation information (including information on currently passable lanes) reported by the vehicle.

[0082] After obtaining the above information, a passable area can be constructed based on the information. This passable area is constructed from the current passable lane information by combining high-precision maps and traffic rules (such as dashed lines being changeable lanes, bus lanes being impassable, etc.). In other words, it is the area where vehicles can currently travel.

[0083] After obtaining the passable area, the first dynamic guide line generation can be performed to obtain the first generated dynamic guide line (i.e., the vehicle guidance information to be adjusted). It should be noted that this step is for generating guide lines in scenarios that require lane changes, such as turning and entering / exiting ramps. The specific method for generating the first dynamic guide line includes: finding the forward distance point P3 (i.e., the guide endpoint position) from the vehicle's current position (i.e., the vehicle's position) by moving a certain distance forward (i.e., the pre-aiming distance); the selection of the "certain distance (i.e., the guide length)" can be adjusted according to the vehicle speed. The higher the vehicle speed, the longer the required "pre-aiming distance"; reflected in the Bézier curve, this means that the control points should be farther apart, and the curve should be smoother overall. The formula for calculating the pre-aiming distance (i.e., the guide length) used in this method is: L=k×v+L0, v: current vehicle speed (m / s), k: gain coefficient (e.g., 1.0~3.0), which determines the strength of the vehicle speed's influence, and L0: minimum pre-aiming distance (e.g., 3.0~10.0 meters), ensuring a reasonable distance even at low speeds or when stopped.

[0084] Step 2: If the guide endpoint is located within the passable area, calculate at least two driving positions based on the guide length, the vehicle position, and the guide endpoint, wherein the at least two driving positions are located between the vehicle position and the guide endpoint.

[0085] Among them, at least two driving positions can be understood as the specific locations that the target vehicle needs to drive to next. These at least two driving positions are used to generate the vehicle guidance information to be adjusted.

[0086] Specifically, after finding the forward distance point P3, this method needs to determine whether the forward distance point P3 is still within the passable area. If it is within the passable area, then a certain distance is found from the tangent direction of the forward distance point to find the backward control point P2 (i.e., the driving position), and a certain distance is found from the tangent direction of the current vehicle pose to find the forward control point P1 (i.e., the driving position). The control points P1 and P2 determine the shape of the curve.

[0087] It should be noted that a common and effective way to determine control points P1 and P2 is to maintain a fixed ratio between the control points and the starting point (P0) / ending point (P3), and this ratio is related to the vehicle speed.

[0088] Regarding the above proportional relationships, this method uses the following empirical formula:

[0089] d1=α_max / (1+β×v)×L

[0090] Where α_max is the maximum ratio at low speed (e.g., 0.5), β is the attenuation coefficient (e.g., 0.1), and L is the aiming distance. Given the positions and directions of P0 and P3, finding the control points P1 and P2 at a certain distance along the tangent is straightforward. The following formula can be used to solve for P1 and P2.

[0091] Among them, P2=(P3.x-d2×cos(θ3),P3.y-d2×sin(θ3)), P1=(P0.x+d1×cos(θ0),P3.y+d1×sin(θ0)).

[0092] In some embodiments, after determining the guide endpoint position according to the travel direction of the target vehicle, the method further includes: if the guide endpoint position is not located in the passable area, determining the passable adjacent lane of the target vehicle according to the lane navigation information of the target road, wherein the passable adjacent lane is a lane adjacent to the current travel lane of the target vehicle and is passable; determining the passable adjacent lane as a passable area, and determining the guide endpoint position in the passable area according to the guide length and the vehicle position information.

[0093] This lane navigation information can be understood as lane-level navigation information generated for the target vehicle.

[0094] Following the previous example, after finding the forward distance point P3, this method needs to determine whether the forward distance point P3 is still within the passable area. If it is not within the passable area, it means that the vehicle needs to change lanes. Therefore, by combining lane-level navigation information, it can be determined that the exploration should start from the adjacent left lane or the adjacent right lane (i.e., the adjacent lane is passable). Then, continue to explore from the adjacent left lane or the adjacent right lane to find the forward distance point P3 (i.e., the guiding endpoint position) that is a certain distance forward from the current position of the vehicle.

[0095] As can be seen from the above embodiments, the embodiments provided in this disclosure improve the real-time performance and accuracy of path guidance by introducing a judgment mechanism on whether the "previous distance point P3 is located in a passable area" during the generation of the guide line, and dynamically adjusting the starting point of the exploration in combination with lane-level navigation information. When the previous distance point P3 is detected to be outside the passable area, the guidance is not simply terminated, but the system actively uses lane-level high-precision maps or navigation information to intelligently determine whether to restart the exploration from the adjacent lane on the left or right. This mechanism allows the vehicle to complete lane change operations in advance and safely when necessary, which conforms to actual driving logic and improves the intelligence level of the assisted driving system. At the same time, the guidance endpoint (i.e., the previous distance point P3) always falls within the passable area, ensuring that the navigation instructions received by the user are continuous and feasible, and improving the overall driving experience.

[0096] Step 3: Based on the vehicle location, the guidance endpoint location, and the at least two driving locations, generate vehicle guidance information for the target vehicle, and determine the vehicle guidance information to be adjusted for the target vehicle based on the vehicle guidance information.

[0097] Specifically, after obtaining the vehicle position, the guide endpoint position, and at least two driving positions, this method can generate vehicle guidance information for the target vehicle through a dynamic guide line algorithm.

[0098] After obtaining vehicle guidance information, it can be directly identified as the vehicle guidance information to be adjusted for the target vehicle; or, after further processing of the vehicle guidance information, the vehicle guidance information to be adjusted for the target vehicle can be obtained.

[0099] In some embodiments, generating vehicle guidance information for the target vehicle based on the vehicle location, the guidance endpoint location, and the at least two driving locations includes: processing the vehicle location, the guidance endpoint location, and the at least two driving locations using a guidance information generation model to obtain the vehicle guidance information for the target vehicle; or generating a curve based on the vehicle location, the guidance endpoint location, and the at least two driving locations using a Bézier curve generation algorithm to obtain the vehicle guidance information for the target vehicle.

[0100] The guidance information generation model can be understood as a network model used to generate vehicle guidance information. The guidance information generation model can be a large model, a deep learning model, etc., and this disclosure does not make any specific limitations on it.

[0101] Following the previous example, after obtaining P0, P1, P2, and P3, this method can combine P0, P1, P2, and P3 to generate dynamic guide lines using cubic Bézier curves. The navigation guide lines (i.e., vehicle guidance information) generated by cubic Bézier curves can intelligently adapt to changes in vehicle speed, providing smooth and stable guidance at high speeds and sensitive and accurate guidance at low speeds.

[0102] Alternatively, after obtaining P0, P1, P2, and P3, these values ​​can be input into the guidance information generation model for reasoning, thereby obtaining the navigation guidance line for the target vehicle. This allows the navigation guidance line to intelligently adapt to changes in vehicle speed, providing smooth and stable guidance at high speeds and sensitive and accurate guidance at low speeds.

[0103] In some embodiments, the vehicle guidance information is a vehicle guide line, and the vehicle guidance information to be adjusted is a vehicle guide line to be adjusted; determining the vehicle guidance information to be adjusted for the target vehicle based on the vehicle guidance information includes: determining a guide extension position within the passable area based on the guide endpoint position and a preset guide extension length; generating an extended guide line for the target vehicle based on the guide endpoint position and the guide extension position; and splicing the extended guide line and the vehicle guide line to obtain the vehicle guidance line to be adjusted for the target vehicle.

[0104] The preset guide extension length can be set according to the actual application scenario. For example, the preset guide extension length can be 20 meters, 50 meters, 100 meters, etc.

[0105] The extended guide position can be understood as the end point of the extended guide line; the extended guide line can be understood as a guide line determined to enhance the display effect.

[0106] Following the previous example, after generating the navigation guide line using a cubic Bézier curve, the guide line can be extended forward from the pre-aiming point P3 to obtain the guide extension position P4, based on the preset guide extension length. Then, an extended guide line is generated based on the pre-aiming point P3 and the guide extension position P4. Finally, the navigation guide line generated by the cubic Bézier curve and the route extended forward from P3 (i.e., the extended guide line) are spliced ​​together to generate the final dynamic guide line (i.e., the vehicle guide line to be adjusted for the target vehicle). This step is to enhance the visual effect of the terminal display, give the guide line a longer extension distance, and improve the driver's experience.

[0107] Step S13: Determine the obstacles corresponding to the target vehicle based on the road information, and adjust the vehicle guidance information to be adjusted based on the obstacles to obtain the target vehicle guidance information.

[0108] Among them, target vehicle guidance information can be understood as vehicle guidance information that needs to be sent to and displayed to the target vehicle.

[0109] Here, an obstacle can be understood as something in the target road that may affect the driving of the target vehicle; for example, the obstacle can be a pedestrian, a non-motorized vehicle, a roadblock, a construction area, a disabled vehicle, or a traffic accident, etc., and this disclosure does not impose specific restrictions on it.

[0110] It should be noted that obstacles can be divided into static obstacles and dynamic obstacles. Static obstacles can be obstacles that are stationary, such as roadblocks, construction areas, and disabled vehicles. Dynamic obstacles can be understood as obstacles that are moving, such as pedestrians, non-motorized vehicles, and animals.

[0111] In some embodiments, determining the obstacle corresponding to the target vehicle based on the road information and adjusting the vehicle guidance information to be adjusted based on the obstacle to obtain the target vehicle guidance information includes: determining the guide lane corresponding to the target vehicle based on the vehicle guidance information to be adjusted, and determining the obstacle corresponding to the driving direction of the target vehicle based on the road information, wherein the guide lane is the lane into which the vehicle guidance information to be adjusted guides the target vehicle; calculating the distance between the obstacle and the guide lane based on the obstacle area of ​​the obstacle and the lane area of ​​the guide lane; determining the vehicle guidance information to be adjusted as the target vehicle guidance information if the distance value is greater than or equal to a preset distance threshold; and adjusting the vehicle guidance information to be adjusted based on the obstacle area if the distance value is less than the preset distance threshold to obtain the target vehicle guidance information.

[0112] The guide lane can be understood as the lane that the target vehicle needs to enter next. The guide lane can be the target vehicle's current lane, left lane, or right lane, etc.

[0113] Among them, the obstacle area can be the coordinate area of ​​the obstacle, and the lane area of ​​the guide lane can be the coordinate area of ​​the guide lane.

[0114] The preset distance threshold can be set according to the actual application scenario. For example, the preset distance threshold can be 3 meters, 4 meters, or the lane width.

[0115] Following the example above, after obtaining the guidance information for the vehicle to be adjusted, the cloud platform used in this method can determine the sensing target objects perceived by the roadside unit from the road information. These sensing target objects include obstacles or traffic facilities (streetlights, traffic signs, etc.) in the target road.

[0116] Then, the cloud platform finds the nearest obstacle in front of the vehicle from the perceived target objects (only the nearest obstacle is warned to avoid information overload on the dynamic guide line); based on the obstacle area of ​​the nearest obstacle and the lane area corresponding to the dynamic guide line, the distance value between the nearest obstacle and the dynamic guide line is calculated. This distance value is used to determine whether the obstacle will affect driving.

[0117] If the distance is greater than the preset distance threshold, it is considered to have no impact, and the dynamic guide line is directly issued; that is to say, the guidance information of the vehicle to be adjusted is determined as the guidance information of the target vehicle.

[0118] If the distance is less than or equal to the preset distance threshold, it is considered to have an impact and the guidance information for the vehicle to be adjusted needs to be adjusted in order to obtain the guidance information for the target vehicle.

[0119] As can be seen from the above embodiments, this method achieves dynamic adjustment of the guide line through a cloud platform; it utilizes roadside units to perceive obstacles and traffic facilities in the target road in real time, focusing on processing the "nearest obstacle in front of the vehicle" to ensure that the guidance information can dynamically reflect the actual road conditions, significantly improving driving safety. By calculating the distance between the nearest obstacle and the lane area where the dynamic guide line is located, and comparing it with a preset safe distance threshold, it determines whether the obstacle has a substantial impact on the current driving path, thus achieving refined and intelligent adjustment of the guide line.

[0120] In some embodiments, adjusting the vehicle guidance information to be adjusted based on the obstacle area to obtain the target vehicle guidance information includes: when the obstacle is a static obstacle, trimming the guide lane of the vehicle guidance information to be adjusted based on the obstacle area of ​​the static obstacle to obtain a trimmed guide lane; and generating target vehicle guidance information based on the vehicle driving information and the road information when it is determined that the drivable lane size corresponding to the target vehicle is smaller than the lane size of the trimmed guide lane; and when the obstacle is a dynamic obstacle, determining a risk area from the guide lane of the vehicle guidance information to be adjusted based on the obstacle area of ​​the dynamic obstacle, adding obstacle area alarm information to the risk area, and obtaining the target vehicle guidance information.

[0121] In some embodiments, when it is determined that the drivable lane size corresponding to the target vehicle is smaller than the lane size of the trimmed guide lane, the vehicle guidance information to be adjusted is determined as the target vehicle guidance information, wherein the vehicle guidance information to be adjusted includes the trimmed guide lane.

[0122] The drivable lane size can be understood as the lane size that the target vehicle can pass through. This drivable lane size includes the drivable lane height and / or drivable lane width. The drivable lane size corresponding to the target vehicle can be set according to the actual application scenario. For example, the drivable lane width can be: the width of the target vehicle + a preset width (such as 200 cm, 400 cm), or 2 meters, 3 meters, etc. The drivable lane height can be: the height of the target vehicle + a preset height (such as 200 cm, 400 cm), or 2 meters, 3 meters, etc.

[0123] The lane dimensions of the trimmed guide lane can be understood as the dimensions of the passable lane corresponding to the trimmed guide lane, which includes lane height and / or lane width.

[0124] The risk area can be understood as the area where there is a traffic risk, that is, the lane area affected by the obstacle area.

[0125] Obstacle area warning information can be understood as the information used in target vehicle guidance information to warn of obstacle areas. This obstacle area warning information can be set according to the actual application scenario. For example, the obstacle area warning information can be: setting the risk area to a specific color (such as red), alarm voice data, or vibration prompts, etc.

[0126] Following the example above, Figure 3 This is a schematic diagram illustrating the adjustment of guide lines in a vehicle guidance information generation method provided in this embodiment of the disclosure. Figure 3 Part 3a in the diagram is a schematic diagram of the dynamic lane change guide line when changing lanes.

[0127] When the distance value is less than or equal to a preset distance threshold, the cloud platform first needs to determine whether the obstacle is a dynamic obstacle or a static obstacle.

[0128] Figure 3 Part 3b illustrates the obstacle avoidance process when the obstacle is static. Based on part 3b, if the obstacle is static, dynamic obstacle avoidance is employed. Specifically, the affected lane area is first trimmed from the passable lane area of ​​the dynamic guide line. Then, it is determined whether the vehicle is still within the passable lane area. If the vehicle is still within the passable lane area, the lane is deemed passable, and a new dynamic guide line (i.e., target vehicle guidance information) is generated based on the vehicle's driving information and road information. The process of regenerating the dynamic guide line is consistent with the method used in the previous embodiment and will not be elaborated further here.

[0129] The method for determining whether a vehicle is still within the traffic area includes: determining whether the size of the drivable lane (e.g., the width of the drivable lane) corresponding to the target vehicle is smaller than the size of the trimmed guide lane (e.g., the width of the lane); if so, the vehicle is still within the traffic area; otherwise, the vehicle is not within the drivable lane area.

[0130] Figure 3 Part 3c is a schematic diagram of dynamic obstacles and unavoidable static obstacles when the obstacle is dynamic. Based on part 3c, if it is determined that the road is impassable or the obstacle is identified as a dynamic obstacle, the dynamic guide line is segmented, the obstacle influence point (i.e., the risk area) is determined from the dynamic guide line, and the guide line is cut off from the obstacle influence point to indicate the path warning of the distance of the vehicle from the obstacle.

[0131] As can be seen from the above embodiments, this method provides a dynamic guide line generation algorithm that directly integrates obstacle information as a constraint into path planning, generating obstacle avoidance guide lines in real time, rather than simply overlaying icons. Through a "path as warning" display design, risk information is intuitively conveyed through changes in guide line shape (offset, narrowing, forking) and color, reducing the driver's cognitive load.

[0132] Step S14: Send the target vehicle guidance information to the target vehicle so that the driver of the target vehicle can control the target vehicle to drive based on the target vehicle guidance information.

[0133] Specifically, the target vehicle is equipped with an information display device that displays the vehicle's guidance information. The cloud platform can send the guidance information to the target vehicle, which can then display the guidance information through the information display device. For example, the information display device can be a voice playback device (such as a speaker) to play prompts guiding the vehicle; or, the information display device can be a vehicle display device (such as a display screen) to display the dynamic guide line.

[0134] In some embodiments, sending the target vehicle guidance information to the target vehicle so that the driver of the target vehicle can control the target vehicle to drive based on the target vehicle guidance information includes: determining the lane display size corresponding to the guide lane in the target vehicle guidance information according to the road map of the target road displayed in the vehicle display device, wherein the vehicle display device is a device configured in the target vehicle for displaying the guide lane; adjusting the display size of the guide lane according to the lane display size to obtain the target vehicle guidance information with adjusted size; and sending the target vehicle guidance information with adjusted size to the target vehicle for display so that the driver of the target vehicle can control the target vehicle to drive based on the target vehicle guidance information.

[0135] The lane display size can be understood as the display size of the guide lane on the vehicle's display device. This lane display size includes the lane display height and / or lane display width.

[0136] Vehicle display devices can be understood as devices in the target vehicle used to display guidance information for the target vehicle, such as displays, projectors, AR-HUDs, etc.

[0137] Following the previous example, the guide lines in this method can be adjusted in conjunction with the lane width changes on the high-precision map. Specifically, the lane display width corresponding to the lane is determined based on the high-precision road map of the target road displayed on the vehicle's display device. Then, the display width of the dynamic guide lines is adjusted according to the lane display width, thereby realizing the adjustment of width changes based on the lane width on the high-precision map. Finally, the adjusted dynamic guide lines are sent to the vehicle for display. The adjusted dynamic guide lines include information on influential obstacles (i.e., the adjusted dynamic guide lines).

[0138] As can be seen from the above embodiments, this disclosure achieves a more realistic, safe, and intelligent vehicle guidance display effect by adaptively adjusting the width of the dynamic guide line driven by a high-precision map and integrating obstacle influence information, thereby improving user experience and enhancing driving safety. Based on the actual lane width of the target road in the high-precision map, the display width of the guide line on the vehicle display device is dynamically adjusted so that the guide line is highly matched with the real lane outline, significantly enhancing the driver's perception accuracy of the vehicle's lateral position and road boundaries.

[0139] The method for generating vehicle guidance information provided in this disclosure is used as an example to illustrate the method for generating dynamic guide lines. Figure 4 This is a schematic diagram illustrating the processing steps of a vehicle guidance information generation method provided in an embodiment of this disclosure, based on... Figure 4 As can be seen, this method is applied to the cloud and includes steps 1 to 11.

[0140] Step 1: Receive the current position and orientation information and lane-level navigation information reported by the vehicle.

[0141] Step 2: Combining high-precision maps and traffic rules, construct the initial passable area (i.e., passable area) from the current passable lane information.

[0142] Step 3: Generate the dynamic guide line for the first time.

[0143] Specifically, the cloud platform can use a dynamic guide line generation algorithm to generate the dynamic guide line for the first time; the specific steps include:

[0144] Step 3.1: Determine the vehicle's current pose P0, and based on the forward aiming distance, move forward a certain distance to the front distance point pose P3, and determine whether P3 is still within the passage area.

[0145] Among them, the front distance point pose P3 can also be simply referred to as the front distance point P3 or P3.

[0146] The forward aiming distance, also known as the aiming distance, can be adjusted according to the vehicle speed. The higher the vehicle speed, the longer the required "aiming distance". This is reflected in the Bézier curve as the control points should be further apart, and the curve will be smoother overall.

[0147] Step 3.2: If P3 is not within the passage area, it means that the vehicle needs to change lanes and continue to move forward from the adjacent lane to obtain the forward distance point P3 from the adjacent lane.

[0148] Step 3.3: If P3 is within the passage area, then search for a rearward control point P2 at a certain distance from the tangent direction of the front distance point, and search for a forward control point P1 at a certain distance from the tangent direction of the vehicle's current pose P0.

[0149] Step 3.4: Use cubic Bézier curves to generate dynamic guide lines by combining P0, P1, P2, and P3.

[0150] Step 3.5: Continue probing forward from P3 to obtain the lane advance distance point, and determine an extended guide line based on P3 and the lane advance distance point. This step is solely for enhancing the visual effect of the terminal display, allowing the guide line to have a longer extension.

[0151] Step 3.6: Connect (i.e. splice) the dynamic guide line and extended guide line generated by the cubic Bézier curve to generate the final dynamic guide line.

[0152] Step 4: Locate the nearest dynamic and static obstacles (i.e., dynamic and static obstacles) in front of the vehicle from the perceived target objects.

[0153] Step 5: Calculate the distance (closest distance) between the nearest obstacle in front of the vehicle and the dynamic guide line; use this distance to determine whether the obstacle will affect driving. A suggested distance is 3 meters, which is approximately the width of the lane.

[0154] Step 6: If the distance is greater than the threshold (3 meters), it is considered to have no impact, and the dynamic guidance line is directly issued.

[0155] Step 7: If the distance is less than or equal to the threshold, it is considered to have an impact. Then it is necessary to determine whether the obstacle is a dynamic obstacle or a static obstacle.

[0156] Step 8: Determine if the obstacle is a static obstacle; if it is a static obstacle, perform dynamic avoidance; the specific method is as follows: first, cut off the lane range affected by the obstacle from the passable area (also known as the passable area), and then determine whether to regenerate the dynamic guide line by judging whether the vehicle can still pass (i.e. whether the vehicle is still in the passable area).

[0157] Step 9: If it is still passable, repeat steps 3-9 to regenerate a new dynamic guide line and send the dynamic guide line.

[0158] Step 10: If the road is impassable or if step 8 determines it to be a dynamic obstacle, then segment the dynamic guide line and cut the guide line from the point of influence of the obstacle to indicate the path warning of the distance between the vehicle and the obstacle.

[0159] Step 11: The dynamic guide line can be combined with the lane adjustment changes of the high-precision map, and finally the dynamic guide line is sent to the vehicle.

[0160] Based on the above steps, this disclosure provides a dynamic guideline fusion display method and system based on multi-source data collaborative perception of vehicles, roads, and cloud. This method and system integrate obstacle information sources (such as temporary construction, illegally parked vehicles, and non-motorized vehicle crossings) and overcomes the problem of perception blind spots. By changing the shape of the guideline, an integrated display effect of "path as warning" is achieved, improving the safety and smoothness of human-machine co-driving. By deeply integrating dynamic obstacle information with navigation guidelines, a real-time obstacle avoidance dynamic guideline is generated, allowing the driver to intuitively understand risks and drivable space.

[0161] In its design, the strategy for handling dynamic obstacles in this disclosure is based on the following three considerations to ensure the practicality and safety of the technology at the current stage.

[0162] 1. Technical Reliability and Confidence Boundaries: The trajectory prediction of dynamic obstacles (such as pedestrians and non-motorized vehicles) inherently involves uncertainty. Using predictions with low confidence directly to generate mandatory obstacle avoidance guide lines may lead to frequent line jumps or misleading results, thereby reducing the system's reliability and user experience. Therefore, this disclosure focuses on handling high-confidence dynamic events (such as stationary obstacles or obstacles with clear movement trends) to ensure the generated guide lines are stable and reliable.

[0163] 2. Role Positioning and Interaction Design of Human-Machine Co-driving: The core positioning of this disclosure is to assist human drivers in decision-making, rather than to replace drivers in fully automated control. When faced with complex dynamic interaction scenarios, different drivers have different reaction preferences. A guideline that attempts to completely define the obstacle avoidance path may conflict with the autonomous decision-making intentions of some drivers, causing interference. Therefore, this disclosure clearly indicates risks and recommends passage spaces to the driver through changes in the shape of the guideline (such as narrowing or offsetting), handing over the final trajectory fine-tuning and control to the driver, achieving harmonious co-driving between human and machine.

[0164] 3. Phased Technological Evolution: This disclosure is an interactive enhancement function designed for manual driving and L2-L3 level human-machine co-driving stages. Its output "dynamic guide line" is essentially a driving suggestion and enhanced situational awareness. This is fundamentally different from the "real-time local trajectory" required for L4 and above autonomous driving, which must be strictly enforced. The latter requires precise control of the spatiotemporal relationship between the vehicle and obstacles, and ensures that the vehicle control system can 100% track the issued trajectory. Decoupling these two aspects allows this disclosure to operate without relying on a high-precision vehicle control interface, possessing stronger platform adaptability and immediate deployment potential.

[0165] Regarding the display of dynamic guide lines: The dynamic guide lines in this disclosure can be projected in 3D on the AR-HUD, or provide tactile feedback through a vibrating steering wheel; through the dynamic guide line generation and display methods in the above embodiments, this disclosure integrates obstacle constraints into the path planning algorithm to generate guide lines with variable shapes, and achieves integrated warning through color and animation.

[0166] Regarding the guide line generation algorithm: This disclosure can use reinforcement learning algorithm to replace traditional optimization algorithm in the path planning process to adaptively learn driving habits; through dynamic drivable corridor reconstruction technology, the drivable area can be adjusted in real time according to the position and size of obstacles and integrated into high-precision map.

[0167] It is understood that the various method embodiments mentioned above in this disclosure can be combined with each other to form combined embodiments without violating the principle and logic. Due to space limitations, this disclosure will not elaborate further. Those skilled in the art will understand that in the above methods of specific implementation, the specific execution order of each step should be determined by its function and possible internal logic.

[0168] In addition, this disclosure also provides a vehicle guidance information generation device, an electronic device, and a computer-readable storage medium, all of which can be used to implement any of the vehicle guidance information generation methods provided in this disclosure. The corresponding technical solutions and descriptions are described in the corresponding section of the method and will not be repeated here.

[0169] Figure 5 This is a block diagram of a vehicle guidance information generation device provided in an embodiment of the present disclosure.

[0170] Reference Figure 5 This disclosure provides a vehicle guidance information generation device, which includes: a region determination module 501, a first information determination module 502, a second information determination module 503, and an information sending module 504.

[0171] The area determination module 501 is used to determine the passable area of ​​the target vehicle based on the target road when receiving the vehicle driving information of the target vehicle and the road information of the target road, wherein the vehicle driving information is information generated by the target vehicle during its travel on the target road.

[0172] The first information determination module 502 is used to determine the vehicle guidance information to be adjusted for the target vehicle based on the vehicle driving information and the passable area.

[0173] The second information determination module 503 is used to determine the obstacles corresponding to the target vehicle based on the road information, and adjust the vehicle guidance information to be adjusted based on the obstacles to obtain the target vehicle guidance information.

[0174] The information sending module 504 is used to send the target vehicle guidance information to the target vehicle so that the driver of the target vehicle can control the target vehicle to drive based on the target vehicle guidance information.

[0175] In some embodiments, the vehicle driving information includes vehicle position and vehicle speed; the first information determining module 502 is further configured to: calculate a guidance length based on the vehicle speed, and determine a guidance endpoint position according to the driving direction of the target vehicle, based on the guidance length and the vehicle position, wherein the guidance length is used to represent the length of the lane guided by the vehicle guidance information; if the guidance endpoint position is located in the passable area, calculate at least two driving positions based on the guidance length, the vehicle position, and the guidance endpoint position, wherein the at least two driving positions are located between the vehicle position and the guidance endpoint position; generate vehicle guidance information for the target vehicle based on the vehicle position, the guidance endpoint position, and the at least two driving positions, and determine the vehicle guidance information to be adjusted for the target vehicle based on the vehicle guidance information.

[0176] In some embodiments, the first information determination module 502 is further configured to: process the vehicle position, the guidance endpoint position, and the at least two driving positions using a guidance information generation model to obtain vehicle guidance information of the target vehicle; or generate a curve based on the vehicle position, the guidance endpoint position, and the at least two driving positions using a Bezier curve generation algorithm to obtain vehicle guidance information of the target vehicle.

[0177] In some embodiments, the first information determining module 502 is further configured to: determine the passable adjacent lane of the target vehicle based on the lane navigation information of the target road when the guiding endpoint position is not located in the passable area, wherein the passable adjacent lane is a lane adjacent to the current driving lane of the target vehicle and is passable; determine the passable adjacent lane as a passable area, and determine the guiding endpoint position in the passable area based on the guiding length and the vehicle position information.

[0178] In some embodiments, the vehicle guidance information is a vehicle guide line, and the vehicle guidance information to be adjusted is a vehicle guide line to be adjusted; the first information determining module 502 is further configured to: determine a guide extension position in the passable area based on the guide endpoint position and a preset guide extension length; generate an extension guide line for the target vehicle based on the guide endpoint position and the guide extension position; and splice the extension guide line and the vehicle guide line to obtain the vehicle guide line to be adjusted for the target vehicle.

[0179] In some embodiments, the second information determining module 503 is further configured to: determine the guiding lane corresponding to the target vehicle based on the vehicle guidance information to be adjusted, and determine the obstacle corresponding to the driving direction of the target vehicle based on the road information, wherein the guiding lane is the lane into which the target vehicle is guided by the vehicle guidance information to be adjusted; calculate the distance value between the obstacle and the guiding lane based on the obstacle area of ​​the obstacle and the lane area of ​​the guiding lane; determine the vehicle guidance information to be adjusted as the target vehicle guidance information if the distance value is greater than or equal to a preset distance threshold; and adjust the vehicle guidance information to be adjusted based on the obstacle area if the distance value is less than the preset distance threshold to obtain the target vehicle guidance information.

[0180] In some embodiments, the second information determining module 503 is further configured to: when the obstacle is a static obstacle, trim the guide lane of the vehicle guidance information to be adjusted according to the obstacle area of ​​the static obstacle to obtain a trimmed guide lane; and when it is determined that the drivable lane size corresponding to the target vehicle is smaller than the lane size of the trimmed guide lane, generate target vehicle guidance information according to the vehicle driving information and the road information; and when the obstacle is a dynamic obstacle, determine a risk area from the guide lane of the vehicle guidance information to be adjusted according to the obstacle area of ​​the dynamic obstacle, add obstacle area alarm information to the risk area, and obtain the target vehicle guidance information.

[0181] In some embodiments, the information sending module 504 is further configured to: determine the lane display size corresponding to the guide lane in the target vehicle guidance information according to the road map of the target road displayed in the vehicle display device, wherein the vehicle display device is a device configured in the target vehicle for displaying the guide lane; adjust the display size of the guide lane according to the lane display size to obtain the target vehicle guidance information after size adjustment; and send the target vehicle guidance information after size adjustment to the target vehicle for display, so that the driver of the target vehicle can control the target vehicle to drive based on the target vehicle guidance information.

[0182] In some embodiments, the vehicle guidance information generation device includes an information receiving module, configured to: receive vehicle driving information sent by the target vehicle, and receive road information of the target lane sent by the roadside unit; or, when the target vehicle sends the vehicle driving information to the roadside unit, receive the vehicle driving information and the road information of the target lane sent by the roadside unit; wherein the vehicle driving information is information collected by the target vehicle through onboard sensors, and the road information is information collected by the roadside unit through configured sensors.

[0183] The vehicle guidance information generation device provided in this embodiment can receive various information data such as vehicle driving information of the target vehicle and road information of the target road, avoiding the problem of insufficient data in the process of generating vehicle guidance information. Furthermore, in the process of generating target vehicle guidance information, the device first determines the passable area of ​​the target vehicle based on the target road, and then determines accurate vehicle guidance information to be adjusted for the target vehicle based on the vehicle driving information and the passable area. Considering the complexity of road conditions and the possibility of obstacles affecting vehicle driving, this method can determine the obstacles corresponding to the target vehicle based on the road information, and adjust the vehicle guidance information to be adjusted based on the obstacles to obtain more accurate target vehicle guidance information. Then, the target vehicle guidance information is sent to the target vehicle, enabling the driver of the target vehicle to control the target vehicle's driving based on more accurate target vehicle guidance information.

[0184] Figure 6 This is a block diagram of an electronic device provided in an embodiment of the present disclosure.

[0185] Reference Figure 6This disclosure provides an electronic device, which includes: at least one processor 601; at least one memory 602; and one or more I / O interfaces 603 connected between the processor 601 and the memory 602; wherein the memory 602 stores one or more computer programs that can be executed by the at least one processor 601, and the one or more computer programs are executed by the at least one processor 601 to enable the at least one processor 601 to perform the above-described vehicle guidance information generation method.

[0186] This disclosure also provides a computer-readable storage medium storing a computer program thereon, wherein the computer program, when executed by a processor, implements the vehicle guidance information generation method described above. The computer-readable storage medium may be volatile or non-volatile.

[0187] This disclosure also provides a computer program product, including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code, wherein when the computer-readable code is run in a processor of an electronic device, the processor in the electronic device executes the above-described vehicle guidance information generation method.

[0188] Those skilled in the art will understand that all or some of the steps, systems, and apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software can be distributed on a computer-readable storage medium, which may include computer storage media (or non-transitory media) and communication media (or transient media).

[0189] As is known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable program instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), static random access memory (SRAM), flash memory or other memory technologies, portable compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, it is known to those skilled in the art that communication media typically contain computer-readable program instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0190] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0191] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0192] The computer program product described herein can be implemented specifically through hardware, software, or a combination thereof. In one alternative embodiment, the computer program product is specifically embodied in a computer storage medium; in another alternative embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0193] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0194] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0195] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0196] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0197] Example embodiments have been disclosed herein, and while specific terminology has been used, it is for illustrative purposes only and should be construed as such, and is not intended to be limiting. In some instances, it will be apparent to those skilled in the art that features, characteristics, and / or elements described in connection with particular embodiments may be used alone, or in combination with features, characteristics, and / or elements described in connection with other embodiments, unless otherwise expressly indicated. Therefore, those skilled in the art will understand that various changes in form and detail may be made without departing from the scope of this disclosure as set forth by the appended claims.

Claims

1. A method for generating vehicle guidance information, characterized in that, include: Upon receiving vehicle driving information of the target vehicle and road information of the target road, the passable area of ​​the target vehicle is determined based on the target road, wherein the vehicle driving information is information generated during the target vehicle's travel on the target road; Based on the vehicle driving information and the passable area, determine the vehicle guidance information to be adjusted for the target vehicle; Based on the road information, the obstacles corresponding to the target vehicle are determined, and the vehicle guidance information to be adjusted is adjusted according to the obstacles to obtain the target vehicle guidance information; The target vehicle guidance information is sent to the target vehicle so that the driver of the target vehicle can control the target vehicle to drive based on the target vehicle guidance information.

2. The method according to claim 1, characterized in that, The vehicle driving information includes vehicle location and speed; The step of determining the vehicle guidance information to be adjusted for the target vehicle based on the vehicle driving information and the passable area includes: The guide length is calculated based on the vehicle speed, and the guide endpoint position is determined according to the travel direction of the target vehicle, the guide length, and the vehicle position. The guide length is used to represent the length of the lane guided by the vehicle guidance information. When the guide endpoint is located within the passable area, at least two driving positions are calculated based on the guide length, the vehicle position, and the guide endpoint, wherein the at least two driving positions are located between the vehicle position and the guide endpoint. Based on the vehicle location, the guidance endpoint location, and the at least two driving locations, vehicle guidance information for the target vehicle is generated, and the vehicle guidance information to be adjusted for the target vehicle is determined based on the vehicle guidance information.

3. The method according to claim 2, characterized in that, The process of generating vehicle guidance information for the target vehicle based on the vehicle location, the guidance endpoint location, and the at least two travel locations includes: Using a guidance information generation model, the vehicle position, the guidance endpoint position, and the at least two driving positions are processed to obtain vehicle guidance information for the target vehicle; or Using a Bézier curve generation algorithm, a curve is generated based on the vehicle position, the guidance endpoint position, and the at least two driving positions to obtain the vehicle guidance information of the target vehicle.

4. The method according to claim 2, characterized in that, After determining the guide endpoint position according to the travel direction of the target vehicle, based on the guide length and the vehicle position, the method further includes: If the guiding endpoint is not located in the passable area, the passable adjacent lane of the target vehicle is determined according to the lane navigation information of the target road, wherein the passable adjacent lane is the lane adjacent to the current driving lane of the target vehicle and is passable. The adjacent passable lanes are identified as passable areas, and the guide endpoint is determined within the passable area based on the guide length and the vehicle position information.

5. The method according to claim 2, characterized in that, The vehicle guidance information is a vehicle guide line, and the vehicle guidance information to be adjusted is the vehicle guide line to be adjusted; The step of determining the vehicle guidance information to be adjusted for the target vehicle based on the vehicle guidance information includes: Based on the guide endpoint position and the preset guide extension length, determine the guide extension position within the passable area; Based on the guide endpoint position and the guide extension position, an extended guide line for the target vehicle is generated; The extended guide line and the vehicle guide line are spliced ​​together to obtain the vehicle guide line to be adjusted for the target vehicle.

6. The method according to any one of claims 1 to 5, characterized in that, The step of determining the obstacle corresponding to the target vehicle based on the road information, and adjusting the vehicle guidance information to be adjusted based on the obstacle to obtain the target vehicle guidance information includes: Based on the vehicle guidance information to be adjusted, the guide lane corresponding to the target vehicle is determined, and based on the road information, the obstacle corresponding to the driving direction of the target vehicle is determined, wherein the guide lane is the lane into which the target vehicle is guided by the vehicle guidance information to be adjusted; Calculate the distance between the obstacle and the guide lane based on the obstacle area and the lane area of ​​the guide lane; If the distance value is greater than or equal to a preset distance threshold, the vehicle guidance information to be adjusted is determined as the target vehicle guidance information; If the distance value is less than a preset distance threshold, the vehicle guidance information to be adjusted is adjusted according to the obstacle area to obtain the target vehicle guidance information.

7. The method according to claim 6, characterized in that, The step of adjusting the vehicle guidance information to be adjusted based on the obstacle area to obtain the target vehicle guidance information includes: When the obstacle is a static obstacle, the guide lane of the vehicle guidance information to be adjusted is trimmed according to the obstacle area of ​​the static obstacle to obtain the trimmed guide lane. If it is determined that the drivable lane size corresponding to the target vehicle is smaller than the lane size of the trimmed guide lane, the target vehicle guidance information is generated according to the vehicle driving information and the road information. When the obstacle is a dynamic obstacle, a risk area is determined from the guide lane of the vehicle guidance information to be adjusted based on the obstacle area of ​​the dynamic obstacle, and obstacle area alarm information is added to the risk area to obtain the target vehicle guidance information.

8. The method according to claim 1, characterized in that, The step of sending the target vehicle guidance information to the target vehicle so that the driver of the target vehicle can control the target vehicle to drive based on the target vehicle guidance information includes: Based on the road map of the target road displayed on the vehicle display device, the lane display size corresponding to the guide lane in the target vehicle guidance information is determined, wherein the vehicle display device is a device configured in the target vehicle for displaying the guide lane; Based on the lane display size, the display size of the guide lane is adjusted to obtain the target vehicle guidance information after size adjustment; The adjusted target vehicle guidance information is sent to the target vehicle for display, so that the driver of the target vehicle can control the target vehicle to drive based on the target vehicle guidance information.

9. The method according to claim 1, characterized in that, The received vehicle driving information of the target vehicle and road information of the target road include: Receive vehicle driving information sent by the target vehicle, and receive road information of the target lane sent by the roadside unit; or When the target vehicle sends the vehicle driving information to the roadside unit, the vehicle driving information and the road information of the target lane sent by the roadside unit are received. The vehicle driving information is information collected by the target vehicle through onboard sensors, and the road information is information collected by the roadside unit through configured sensors.

10. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores one or more computer programs that can be executed by the at least one processor, the one or more computer programs being executed by the at least one processor to enable the at least one processor to perform the method as described in any one of claims 1-9.

Images