Vehicle control method and device, equipment, storage medium and program product

Abstract

The invention discloses a vehicle control method and device, equipment, a storage medium and a program product, and relates to the technical field of vehicle control, and the method comprises the steps: determining a second driving path corresponding to an opposite vehicle under the condition that a fork exists in front of a current driving road of the vehicle and a first driving path of the vehicle is straight at the fork; under the condition that the second driving path and the first driving path intersect at the fork intersection, scene information around the fork intersection is acquired; according to the scene information, predicting the driving duration of the vehicle going straight to pass through the fork; and under the condition that the driving duration is larger than the duration threshold value, the vehicle is controlled to be braked before entering the fork road junction. Therefore, the possibility of intersection and collision of the vehicle and the opposite vehicle in the intersection is fundamentally avoided, subsequent traffic flow congestion and potential safety hazards caused by incapability of passing after intersection are further avoided, and the passing efficiency and the passing safety are improved.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, and in particular to vehicle control methods, devices, equipment, storage media, and program products. Background Technology

[0002] With the increase in car ownership and the increasing complexity of road traffic networks, intersections (such as crossroads and T-junctions) are key nodes where traffic flows converge. Vehicles going straight have the right-of-way, but when intersection conditions are complex, if vehicles going straight insist on proceeding, they may meet oncoming vehicles at the intersection, affecting traffic safety and efficiency. Therefore, how to control vehicles to avoid congestion and safety hazards caused by oncoming vehicles meeting at intersections has become an urgent problem to solve. Summary of the Invention

[0003] The main objective of this application is to provide a vehicle control method, device, equipment, storage medium, and program product, which aims to solve the technical problem that when the road conditions at a fork in the road are complex, straight-going vehicles may meet oncoming vehicles at the fork in the road, causing traffic congestion.

[0004] To achieve the above objectives, this application proposes a vehicle control method, the method comprising: If there is a fork in the road ahead of the vehicle's current route, and the vehicle's first route is to go straight at the fork, determine the second route for the oncoming vehicle. When the second driving path intersects with the first driving path at the fork in the road, obtain scene information around the fork in the road; Based on the scenario information, predict the travel time for the vehicle to travel straight through the intersection; If the driving time exceeds a time threshold, the vehicle is controlled to stop before entering the fork in the road.

[0005] In one embodiment, predicting the travel time of the vehicle traveling straight through the intersection based on the scene information includes: Based on the scene information, determine the passable width of the current driving road and the status information of the obstacles on the current driving road; Based on the passable width and the status information corresponding to the obstacles, the travel time for the vehicle to pass straight through the intersection is predicted.

[0006] In one embodiment, after predicting the travel time of the vehicle traveling straight through the intersection based on the scene information, the method further includes: Determine the sample travel time of a sample vehicle traveling straight through a sample fork in the road, wherein the sample passable width of the sample road where the sample vehicle is located is a width threshold, and the moving speed of the sample obstacle on the sample road at the sample location is a speed threshold. The driving time of the sample is determined as the duration threshold.

[0007] In one embodiment, determining the second travel path corresponding to the oncoming vehicle includes: Determine the status of the left turn signal of the oncoming vehicle and its parking position at the intersection; If the left turn signal is on and the parking position is within the preset area, the second driving path is determined to be a left turn at the intersection.

[0008] In one embodiment, determining the second travel path corresponding to the oncoming vehicle includes: Determine the left turn signal status, parking position, and traffic flow corresponding to the target road of the oncoming vehicle, wherein the target road intersects with the current driving road at the intersection and is located on the right side of the vehicle; If the left turn signal is on, the parking position is in a preset area, and the traffic flow is greater than the traffic flow threshold, the second driving path is determined to be a left turn at the intersection.

[0009] In one embodiment, after controlling the vehicle to stop before entering the fork in the road, the method further includes: If the second driving path does not intersect with the first driving path at the fork in the road, or if the driving time is less than or equal to the time threshold, the braking control on the vehicle is released.

[0010] Furthermore, to achieve the above objectives, this application also proposes a vehicle control device, the vehicle control device comprising: The determination module is used to determine the second driving path of the oncoming vehicle when there is a fork in the road ahead of the vehicle's current driving road and the vehicle's first driving path is to go straight at the fork in the road; The acquisition module is used to acquire scene information around the fork in the road when the second driving path intersects with the first driving path at the fork in the road. The prediction module is used to predict the travel time of the vehicle traveling straight through the intersection based on the scene information. The control module is used to control the vehicle to stop before entering the fork in the road if the driving time exceeds a time threshold.

[0011] In one embodiment, the prediction module is configured to: Based on the scene information, determine the passable width of the current driving road and the status information of the obstacles on the current driving road; Based on the passable width and the status information corresponding to the obstacles, the travel time for the vehicle to pass straight through the intersection is predicted.

[0012] In one embodiment, a first processing module is further included, configured to: Determine the sample travel time of a sample vehicle traveling straight through a sample fork in the road, wherein the sample passable width of the sample road where the sample vehicle is located is a width threshold, and the moving speed of the sample obstacle on the sample road at the sample location is a speed threshold. The driving time of the sample is determined as the duration threshold.

[0013] In one embodiment, the determining module is configured to: Determine the status of the left turn signal of the oncoming vehicle and its parking position at the intersection; If the left turn signal is on and the parking position is within the preset area, the second driving path is determined to be a left turn at the intersection.

[0014] In one embodiment, the determining module is configured to: Determine the left turn signal status, parking position, and traffic flow corresponding to the target road of the oncoming vehicle, wherein the target road intersects with the current driving road at the intersection and is located on the right side of the vehicle; If the left turn signal is on, the parking position is in a preset area, and the traffic flow is greater than the traffic flow threshold, the second driving path is determined to be a left turn at the intersection.

[0015] In one embodiment, a second processing module is further included, for: If the second driving path does not intersect with the first driving path at the fork in the road, or if the driving time is less than or equal to the time threshold, the braking control on the vehicle is released.

[0016] In addition, to achieve the above objectives, this application also proposes a vehicle control device, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the vehicle control method as described above.

[0017] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and which, when executed by a processor, implements the steps of the vehicle control method described above.

[0018] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the vehicle control method described above.

[0019] One or more technical solutions proposed in this application have at least the following technical effects: The application prioritizes determining whether the second travel path of the oncoming vehicle and the first travel path of the vehicle will intersect at the intersection before the vehicle enters the fork in the road. This enables early identification of conflict risks and allows sufficient response time for subsequent intervention measures. Then, based on the scenario information, the time required for the vehicle to proceed straight through the fork is determined. If the vehicle cannot quickly pass through the fork, it is controlled to brake in advance before entering the fork to yield to oncoming vehicles. This fundamentally avoids the possibility of a collision between the vehicle and oncoming vehicles within the intersection, thereby preventing subsequent traffic congestion and safety hazards caused by the inability to pass after the intersection, and improving traffic efficiency and safety. Attached Figure Description

[0020] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0021] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating an embodiment of the vehicle control method of this application. Figure 2 This is a flowchart illustrating Embodiment 2 of the vehicle control method of this application; Figure 3 This is a flowchart illustrating Embodiment 3 of the vehicle control method of this application; Figure 4 This is a schematic diagram of the module structure of the vehicle control device according to an embodiment of this application; Figure 5 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the vehicle control method in the embodiments of this application.

[0023] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0024] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0025] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0026] With the development of intelligent driving technology, City Navigation Guided Pilot (CNGP) systems have gradually become widespread. Currently, advanced CNGP systems typically integrate data from multiple sensors, such as LiDAR, millimeter-wave radar, and cameras, into their perception modules to perceive the surrounding environment. Their decision-making modules tend to employ pre-trained large-scale models (such as deep learning models) to achieve end-to-end processing from environmental perception to driving decisions, aiming to improve the overall performance of the system.

[0027] However, existing systems of this type have a significant limitation: their decision-making logic essentially simulates the reactions of human drivers based on real-time information. Predictions of the behavior of other road users (especially oncoming vehicles) typically rely solely on the target vehicle's current physical state information, such as steering angle, speed, and acceleration, to predict its short-term trajectory. This approach lacks a deep understanding and predictive ability regarding the driver's intentions. This deficiency becomes glaringly apparent in certain complex scenarios. For example, in a typical narrow road traffic scenario: a vehicle is traveling on a two-way road, but one lane on each side is occupied by parked cars, leaving only enough space for two vehicles to pass side-by-side. At this point, there is a fork in the road to the right of the vehicle (e.g., leading to a car wash, repair shop, or parking lot), while a slow-moving object (such as a pedestrian or tricycle) or a static obstacle is located a short distance ahead of the fork in the road, not far from the fork. Simultaneously, a vehicle in the oncoming lane slows down and stops before the fork, activating its turn signal to indicate its intention to enter the fork.

[0028] Faced with this scenario, the typical decision-making process using existing technology is for the vehicle to continue along its lane until it is blocked by a slow-moving object ahead and stops. However, this action would precisely block the path of oncoming vehicles entering the intersection. As a result, the vehicle is "sandwiched" between the oncoming vehicle and the slow-moving object ahead, unable to move forward or around it, leading to traffic congestion. The essence of the problem is that existing systems cannot recognize the explicit intention of the oncoming vehicle driver (i.e., to enter the intersection) and make a cooperative decision to "yield." If this intention could be predicted, the most reasonable strategy for the vehicle would be to stop and wait at an appropriate position before the intersection, allowing the oncoming vehicle to pass first, and then the vehicle could safely bypass the slow-moving object ahead, thus efficiently and smoothly navigating the area.

[0029] Therefore, this application provides a solution where, when there is a fork in the road ahead of the vehicle's current driving path and the vehicle's first driving path is to go straight through the fork, a second driving path corresponding to the oncoming vehicle is determined; when the second driving path intersects with the first driving path at the fork, scene information around the fork is obtained; based on the scene information, the driving time for the vehicle to go straight through the fork is predicted; and if the driving time exceeds a time threshold, the vehicle is controlled to stop before entering the fork.

[0030] As can be seen from the above embodiments, this application prioritizes determining whether the second driving path of the oncoming vehicle and the first driving path of the vehicle will intersect at the intersection before the vehicle enters the intersection, achieving early identification of conflict risks and reserving sufficient response time for subsequent intervention measures. Then, based on the scenario information, it determines the time required for the vehicle to proceed straight through the intersection. If the vehicle cannot quickly pass through the intersection, it controls the vehicle to brake in advance before entering the intersection to yield to oncoming vehicles. This fundamentally avoids the possibility of collisions between the vehicle and oncoming vehicles within the intersection, thereby preventing subsequent traffic congestion and safety hazards caused by the inability to pass after the intersection, and improving traffic efficiency and safety.

[0031] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or vehicle control device capable of performing the above functions. The following description uses a vehicle control device as an example to illustrate this embodiment and the subsequent embodiments.

[0032] Based on this, embodiments of this application provide a vehicle control method, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the vehicle control method of this application. Figure 1 As shown, the vehicle control method includes steps S10 to S40: Step S10: If there is a fork in the road ahead of the vehicle's current driving road and the vehicle's first driving path is to go straight at the fork in the road, determine the second driving path corresponding to the oncoming vehicle.

[0033] The current driving route refers to the lane and road that the vehicle is currently traveling on, which can be determined by combining onboard positioning modules (such as GPS or Beidou positioning) with high-definition map data.

[0034] Among them, a fork in the road refers to a branch intersection formed by the current road and other roads (such as side roads or turning lanes of oncoming lanes), including branch areas of T-shaped intersections, Y-shaped intersections, and crossroads. Its location can be identified by matching positioning data with map data, or determined by detecting changes in road markings (such as directional arrows and lane dividing lines) through vehicle cameras and radar.

[0035] In some embodiments, a fork in the road may also be referred to as a crossroads, a fork in the road, etc. This application does not limit this terminology.

[0036] In some embodiments, the determination method for the first driving path to be straight is as follows: the steering angle is detected by the vehicle's steering wheel angle sensor. If the steering angle is within a preset straight-ahead threshold range (e.g., ±5°), and the vehicle's driving direction is consistent with the extension direction of the current road, then the first driving path is determined to be straight. Alternatively, a preset driving route is obtained through the vehicle navigation system. If the driving instruction at the corresponding intersection in the preset route is straight, then the first driving path is directly determined to be straight.

[0037] Among them, oncoming vehicles refer to vehicles that are traveling in the opposite direction to this vehicle and are located in the opposite lane (or adjacent oncoming passable area) of the current driving road. They can be detected and identified by vehicle-mounted radar (such as millimeter-wave radar, lidar), cameras and vehicle-to-everything (V2X) communication modules.

[0038] In one possible implementation, step S10 may include steps A11-A12: Step A11: Determine the status of the oncoming vehicle's left turn signal and its parking position at the intersection.

[0039] In some embodiments, the left turn signal status detection can be achieved in two ways: First, by receiving the turn signal status signal sent by the oncoming vehicle through a V2X communication module, wherein the turn signal status signal is generated and sent by the oncoming vehicle's body control system. Second, by acquiring image information of the oncoming vehicle through an onboard camera, and using image recognition algorithms (such as deep learning object detection algorithms) to identify the illumination status of the left turn signal (e.g., detecting the brightness and color changes of the left-side light group of the oncoming vehicle in the image and comparing it with the unlit state).

[0040] The stopping position refers to the stopping position of an oncoming vehicle near the intersection. When an oncoming vehicle is currently stationary, the stopping position is its current location. When an oncoming vehicle is currently moving, its impending stopping position can be predicted based on its status (such as speed, braking operation, and distance from the intersection), and this impending stopping position can be determined as the stopping position of the oncoming vehicle.

[0041] Step A12: If the left turn signal is on and the parking position is within the preset area, determine the second driving path as turning left at the intersection.

[0042] The preset area can be a region where oncoming vehicles can stop and wait to turn left at a fork in the road. For example, the preset area can be an area extending 0-5 meters in the direction of oncoming traffic and 0-3 meters in the opposite direction of oncoming traffic, based on the stop line of the oncoming lane. This application does not impose specific limitations on this.

[0043] It should be noted that if the parking position of the oncoming vehicle falls into the preset area and the left turn signal is on, it indicates that the oncoming vehicle intends to turn left, and therefore the second driving path is determined to be a left turn.

[0044] In this embodiment, by detecting the status of the left turn signal and the parking position of the oncoming vehicle, the second driving path corresponding to the oncoming vehicle can be accurately determined to be a left turn at the intersection.

[0045] In another possible implementation, step S10 may include steps B11-B12: Step B11: Determine the status of the left turn signal of the oncoming vehicle, its parking position, and the traffic flow corresponding to the target road. The target road intersects with the current road at a fork in the road and is located on the right side of the vehicle.

[0046] The target road refers to the road that oncoming vehicles will enter after turning left, and its location can be determined through map data.

[0047] Traffic flow refers to the number of vehicles passing through the intersection area of ​​the target road and the fork in the road per unit time. It can be obtained by detecting the traffic situation on the target road through vehicle cameras and radar, or by receiving traffic flow data sent by traffic control equipment (such as intersection monitoring and traffic signal controllers) through V2X communication, and counting the number of vehicles passing through within a preset time window (such as 10 minutes).

[0048] In some embodiments, if there are parking lots, car washes, repair shops, etc. within 100 meters of the target road intersection, the traffic flow on the target road will be higher, and the probability of oncoming vehicles turning left will increase.

[0049] Step B12: If the left turn signal is on, the parking position is in the preset area, and the traffic flow is greater than the traffic flow threshold, determine the second driving path as turning left at the intersection.

[0050] The traffic flow threshold is a pre-set critical value for traffic volume, and its value is determined according to the road type. For example, the traffic flow threshold for urban arterial roads is set at 15 vehicles / 10 seconds, while the traffic flow threshold for suburban roads is set at 5 vehicles / 10 seconds.

[0051] It should be noted that when an oncoming vehicle's left turn signal is illuminated, its parking position is within the preset area, and the traffic flow on the target road exceeds the traffic flow threshold, it indicates that the oncoming vehicle has an urgent need to turn left. Therefore, the second driving path is determined to be a left turn. If the traffic flow is less than or equal to the traffic flow threshold, the judgment can be temporarily postponed to avoid misjudgment that could cause the vehicle to slow down or stop unnecessarily.

[0052] It is understandable that, compared to the second implementation method, the first implementation method of step S10 provided above only needs to determine whether the oncoming vehicle is turning left based on its left turn signal and parking position. This makes the judgment logic simpler and more efficient, and is suitable for suburban or rural roads with low traffic volume and simple traffic conditions. However, the second implementation method further considers whether the road the oncoming vehicle is about to enter is a section with high traffic volume, making the judgment conditions more comprehensive and accurate. This method is suitable for urban arterial roads or intersections with high traffic volume and complex traffic conditions.

[0053] The above are only two feasible implementations of step S10 provided in this embodiment. This embodiment does not specifically limit the specific implementation of step S10.

[0054] Step S20: When the second driving path intersects with the first driving path at a fork in the road, obtain scene information around the fork in the road.

[0055] The intersection of the second and first driving paths refers to the overlap of their meeting areas at a fork in the road. Specifically, a collision may occur when the vehicle proceeds straight through the fork and when an oncoming vehicle turns left. In some embodiments, the intersection determination can be achieved using a path planning algorithm: based on the first and second driving paths, the intersection of the two paths within the fork area is calculated. If the intersection is not empty, an intersection is determined to exist; if the intersection is empty, no intersection is determined to exist.

[0056] Among them, the scene information around the fork in the road refers to various environmental parameters that affect the vehicle's straight passage through the fork in the road, including but not limited to the following: (1) Parameter information of the current driving road: such as the number of current driving lanes, the passable width, the road surface condition (such as dry, wet, snow, ice), and the type of road markings (such as solid lines, dashed lines, and directional arrows); (2) Obstacle information: the types of obstacles on the current driving road and in the intersection area of ​​the fork in the road (such as pedestrians, non-motorized vehicles, stationary vehicles, and construction barriers), the location coordinates of obstacles, and the speed and direction of movement of obstacles; (3) Traffic signal information: the status of traffic lights at the fork in the road (red light, green light, yellow light) and the remaining duration of the traffic lights; (4) Environmental meteorological information: such as weather conditions (sunny, rainy, foggy, snowy) and visibility (such as visibility less than 200 meters in foggy weather); (5) Other vehicle information: the driving speed, position, and driving direction of other vehicles around the fork in the road, except for oncoming vehicles.

[0057] In some embodiments, visual information such as road markings, traffic lights, and obstacle images can be acquired via vehicle-mounted cameras; three-dimensional information such as distance, speed, and position of obstacles can be detected via millimeter-wave radar and lidar; meteorological information can be acquired via vehicle-mounted temperature and humidity sensors and rain sensors; traffic signals and traffic flow information sent by other vehicles and traffic control equipment can be received via V2X communication modules; and inherent road parameters (such as lane width and intersection shape) can be obtained via high-definition maps. Multi-sensor fusion can improve the accuracy and completeness of scene information and avoid detection errors from single sensors.

[0058] The core objective of this step is to collect intersection scene information when it is determined that there is a risk of intersection between the travel paths of oncoming vehicles and the travel paths of the vehicle itself, so as to provide data support for subsequent travel time prediction and control decisions.

[0059] Step S30: Based on the scene information, predict the travel time for the vehicle to travel straight through the intersection.

[0060] The core purpose of this step is to accurately predict the time required for the vehicle to travel straight through the intersection from its current location based on the collected scene information, providing a basis for subsequent judgments on whether to brake.

[0061] "Going straight through the intersection" refers to the process of the vehicle starting from its current position and traveling to the end of the intersection area, i.e., completely exiting the intersection risk area.

[0062] In one possible implementation, the prediction logic for travel time is to calculate the maximum permissible speed of the vehicle by combining key scenario information such as the passable width of the current road and the moving speed of obstacles, and then determine the travel time based on the distance between the current position and the end of the fork in the road.

[0063] For example, if the current road is wide enough to pass (e.g., greater than 4 meters) and free of obstacles, the vehicle can maintain its current speed (e.g., 60 km / h) to pass through the intersection, and the travel time = distance / speed. If there are moving obstacles (e.g., pedestrians crossing the road), the vehicle must slow down and give way, at which point the maximum permissible speed is reduced (e.g., reduced to 30 km / h), and the travel time increases accordingly.

[0064] Step S40: If the driving time exceeds the time threshold, control the vehicle to stop before entering the intersection.

[0065] The time threshold can be a pre-set maximum allowable time for the vehicle to safely pass through the intersection. Its value can be related to factors such as the size of the intersection, traffic flow, and vehicle type. For example, the time threshold for a small car at an urban T-junction is set to 20 seconds, and the time threshold for a large truck is set to 30 seconds.

[0066] A travel time exceeding a certain threshold indicates that the vehicle spends an extended period crossing the intersection. During this time, if oncoming left-turning vehicles also enter the intersection area, the vehicle may be sandwiched between the oncoming vehicle and a slow-moving obstacle ahead, unable to move forward or around, leading to traffic congestion. In this situation, the vehicle control system needs to calculate the required braking force based on the current speed and the distance to the stop line at the intersection, and adopt a gradual braking strategy (such as first decelerating to 20 km / h, and then gradually stopping) to avoid sudden braking that could cause loss of control or rear-end collisions. Simultaneously, the stopping position must be before the stop line at the intersection (e.g., 1-2 meters away) to ensure that it does not impede the passage of other vehicles.

[0067] In this embodiment, before the vehicle enters the intersection, it is first determined whether the second driving path of the oncoming vehicle and the first driving path of the vehicle will intersect at the intersection. This achieves early identification of conflict risks and provides sufficient response time for subsequent intervention measures. Then, based on the scenario information, the time required for the vehicle to proceed straight through the intersection is determined. If the vehicle cannot quickly pass through the intersection, it is controlled to brake in advance before entering the intersection to yield to oncoming vehicles. This fundamentally avoids the possibility of collisions between the vehicle and oncoming vehicles within the intersection, thereby preventing subsequent traffic congestion and safety hazards caused by the inability to pass after the intersection, and improving traffic efficiency and safety.

[0068] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 . Figure 2 This is a flowchart illustrating the second embodiment of the vehicle control method of this application, as shown below. Figure 2 As shown, step S30 also includes steps S31 to S32: Step S31: Based on the scene information, determine the passable width of the current driving road and the status information of the obstacles on the current driving road.

[0069] The passable width refers to the effective width within the current driving lane that allows vehicles to pass safely. In some embodiments, the left and right boundaries (such as lane lines, shoulders, and guardrails) of the current driving lane can be scanned using LiDAR to obtain the coordinate information of the boundaries, and the distance between the two boundaries can be calculated to obtain the passable width.

[0070] The state information corresponding to the obstacle is a multi-dimensional parameter set characterizing the obstacle's own attributes and motion characteristics. Its core function is to accurately determine the degree of interference of the obstacle with the straight-through passage of the vehicle. In some embodiments, it includes the following core dimensions: 1. Obstacle type: determined by image information collected by the vehicle-mounted camera and combined with deep learning classification algorithms, including different types such as pedestrians, non-motorized vehicles (bicycles, electric bicycles), motorized vehicles (small cars, large cars), and stationary obstacles (construction barriers, roadblocks, debris). Different types of obstacles have different avoidance priorities and avoidance strategies (e.g., pedestrians have the highest avoidance priority and require significant deceleration; small stationary debris can be bypassed at low speed); 2. Obstacle position coordinates: the real-time position of the obstacle in the road coordinate system is detected by lidar to determine the relative distance and relative orientation (e.g., directly in front, left, right) of the obstacle to the vehicle, and whether the obstacle is on the straight-through path of the vehicle; 3. Obstacle movement parameters: including moving speed (the relative speed of the obstacle is detected by millimeter-wave radar and the absolute speed is calculated by combining it with the vehicle's driving speed), moving direction (the movement trajectory is calculated by continuous multi-frame position data to determine the angle between the moving direction and the vehicle's straight-line direction, such as in the same direction, opposite direction, or perpendicular intersection); 4. Obstacle size parameters: the length, width, and height of the obstacle are obtained by laser radar scanning to determine whether the obstacle can be bypassed (e.g., spilled objects with a width of less than 0.3 meters can be bypassed, while stationary vehicles with a width of more than 1 meter cannot be bypassed); 5. Obstacle dynamic status: determining whether the obstacle is in a moving state (dynamic) or a stationary state (static). For static obstacles, it is necessary to determine whether they are temporarily occupying the road (e.g., temporary parking) or permanently occupying the road (e.g., construction barriers).

[0071] In some embodiments, obstacle state information can be acquired using a "multi-sensor fusion + dynamic update" approach: obstacle type identification is achieved through cameras, position and size information is obtained through LiDAR, and motion parameters are obtained through millimeter-wave radar. The data from each sensor are subjected to redundancy verification and error correction through data fusion algorithms (such as Kalman filtering) to ensure information accuracy. Simultaneously, obstacle state information is updated in real time with an update cycle of 100ms to adapt to dynamic changes in obstacles (such as pedestrians suddenly crossing the road or vehicles changing lanes).

[0072] Step S32: Predict the driving duration for the vehicle to go straight through the fork intersection according to the passable width and the status information corresponding to the obstacle.

[0073] In some embodiments, the basic passing speed of the vehicle can be determined based on the passable width, and then combined with the dimensional parameters of the obstacle status information, the basic passing speed is dynamically corrected. Finally, according to the corrected actual passing speed and the required passing distance, the driving duration is calculated.

[0074] First, a mapping relationship between the passable width and the basic passing speed can be established in advance. Based on the passable width, the basic passing speed is obtained by querying the mapping relationship table. It should be noted that the wider the passable width, the higher the basic passing speed; the narrower the passable width, the lower the basic passing speed, ensuring the safe passage of the vehicle within the effective width.

[0075] After that, according to the dimensional parameters of the obstacle status information, a correction coefficient is determined to adjust the basic passing speed. The correction formula is: V = V × K, where K is the comprehensive correction coefficient (0 < K ≤ 1), and the value of K is determined according to the degree of interference of the obstacle to passing. The greater the interference, the smaller the value of K. The specific correction rules may include at least one of the following: (1) Obstacle type correction: The K value corresponding to pedestrians and non-motor vehicles is 0.3 - 0.5 (significant deceleration required); the K value corresponding to large motor vehicles is 0.4 - 0.6; the K value corresponding to small motor vehicles is 0.5 - 0.7; the K value corresponding to stationary small-sized spillage is 0.8 - 0.9 (minor deceleration).

[0076] (2) Obstacle position correction: When the obstacle is directly in front of the straight path, the K value is 0.2 - 0.4; when it is on the left / right non-straight path, the K value is 0.7 - 0.9; when the distance from the vehicle is less than 10 meters, the K value is reduced by 0.2; when the distance is greater than 30 meters, the K value remains unchanged.

[0077] (3) Motion parameter correction: When the moving direction of the obstacle is perpendicular to the straight direction of the vehicle (such as pedestrians crossing), the K value is 0.2 - 0.3; when moving in the opposite direction, the K value is 0.4 - 0.5; when moving in the same direction, the K value is 0.7 - 0.8; when the moving speed is greater than 15 km / h, the K value is reduced by 0.1.

[0078] (4) Dynamic state correction: The K value of dynamic obstacles is reduced by 0.2 compared to the same type of static obstacles; the K value of temporary road occupation static obstacles (such as temporary parking) is 0.6 - 0.7; for permanent road occupation static obstacles (such as construction fences), the passable width needs to be re-evaluated and then the basic speed is determined.

[0079] In some embodiments, if K has multiple values, the minimum value of K is used to determine the final sum correction coefficient, and then the adjusted traffic speed is determined.

[0080] It should be noted that if there is an obstacle directly ahead of the vehicle's straight-ahead path, the vehicle's actual speed after encountering the obstacle must not exceed the obstacle's speed. That is, the vehicle's maximum speed limit equals the speed of the obstacle directly ahead. Therefore, after adjusting the base speed based on a correction factor, the corrected speed is compared with the maximum speed limit, and the smaller of the two is taken as the vehicle's final speed.

[0081] Finally, using the vehicle positioning module and high-definition map data, the distance between the current vehicle position and the end of the intersection is determined. Then, based on the distance and the determined travel speed of the vehicle, the travel time is determined.

[0082] In this embodiment, by determining the passable width and obstacle status information based on the scene information of the fork in the road, the vehicle travel time can be accurately calculated, which significantly reduces the prediction deviation compared to single parameter prediction.

[0083] In one feasible implementation, after step S30, the method further includes: determining the sample travel time of the sample vehicle traveling straight through the sample fork in the road, wherein the sample passable width corresponding to the sample road where the sample vehicle is located is a width threshold, the moving speed of the sample obstacle on the sample road at the sample position is a speed threshold, and then determining the sample travel time as a duration threshold.

[0084] Among them, the sample vehicles can be of the same type as the current vehicles (such as all being small passenger cars or all being large freight trucks) to ensure that the parameters such as vehicle power performance, braking performance, and body size are matched, and to avoid the sample duration being inapplicable due to differences in vehicle type.

[0085] Among them, the sample bifurcation intersections are bifurcation intersections of the same type as the current bifurcation intersections. The geometric parameters of the sample bifurcation intersections (such as intersection width, intersection angle, number of guiding lanes) deviate from those of the current bifurcation intersections by no more than 10%, to ensure the consistency of the intersection environment.

[0086] The sample road is the same as the road the vehicle is currently traveling on.

[0087] The passable width of the sample is the same as the passable width of the road currently in which the vehicle is traveling.

[0088] The width threshold is the width that allows two vehicles to pass side-by-side. For example, the width threshold can be between 3 meters and 5.2 meters. This application does not impose any limitations on this.

[0089] The sample location refers to the position of the obstacle on the sample road. The sample location can be a preset position that affects the passage of this vehicle.

[0090] The speed threshold can be either 5 km / h or 3 km / h.

[0091] In some embodiments, the sample driving time can be collected multiple times by changing the sample position of the sample obstacle. Then, the collected multiple sample driving times are cleaned to remove outliers (such as extreme durations caused by sudden braking or acceleration due to driver operation errors). The average value of the remaining valid sample time is calculated, and this average value is the sample driving time.

[0092] In this implementation, sample data is collected through standardized sample scenarios to ensure the rationality and adaptability of the duration threshold, and to avoid control failure caused by threshold settings that are too wide or too narrow.

[0093] Based on the first embodiment of this application, in the third embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 3 , Figure 3 This is a flowchart illustrating the third embodiment of the vehicle control method of this application, as shown below. Figure 3 As shown, after step S40, step S50 is also included: Step S50: If it is detected that the second driving path and the first driving path do not intersect at the intersection, or the driving time is less than or equal to the time threshold, the braking control of the vehicle is released.

[0094] The method for determining that the second driving path does not intersect with the first driving path is the same as the method for determining the intersection in step S20, that is, the intersection of the two paths is calculated in real time by the path planning algorithm. If the intersection is empty, it is determined that there is no intersection.

[0095] If the driving time is less than or equal to the time threshold, it means that the vehicle can pass through the intersection within a safe time without causing traffic congestion, and there is no need to continue braking.

[0096] In some embodiments, the specific process of releasing the braking control can be as follows: the vehicle control system sends a release command to the braking system, the braking system gradually releases the braking pressure, and at the same time, the power system gradually restores power output according to the current road conditions (such as whether the road is clear and whether there are other obstacles), so that the vehicle slowly accelerates to the original driving speed or the current maximum allowed driving speed. During this process, the vehicle control system continuously monitors scene information and the driving status of oncoming vehicles. If a crossover risk is detected again and the driving time exceeds the duration threshold, the braking control can be restarted to ensure driving safety.

[0097] In this embodiment, during vehicle braking, the system continuously monitors whether the second and first driving paths intersect at the intersection and whether the travel time is less than or equal to a time threshold. Once the intersection risk is eliminated or the travel time meets the requirements, the vehicle's normal driving state is promptly restored. This avoids congestion at intersections, preventing increased collision risks, and also prevents reduced traffic efficiency due to prolonged waiting times.

[0098] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the vehicle control method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0099] This application also provides a vehicle control device, please refer to... Figure 4 The vehicle control device includes: The determination module 401 is used to determine the second driving path of the oncoming vehicle when there is a fork in the road ahead of the vehicle's current driving road and the vehicle's first driving path is to go straight at the fork in the road. The acquisition module 402 is used to acquire scene information around the intersection when the second driving path and the first driving path intersect at the intersection. The prediction module 403 is used to predict the travel time of a vehicle going straight through a forked intersection based on scene information. The control module 404 is used to control the vehicle to stop before entering the intersection if the driving time exceeds a time threshold.

[0100] In one embodiment, the prediction module 403 is configured to: Based on the scene information, determine the passable width of the current driving road and the status information of the obstacles on the current driving road; Based on the passable width and the status information of the obstacles, the travel time for a vehicle to pass through the intersection in a straight line is predicted.

[0101] In one embodiment, a first processing module is further included, configured to: Determine the sample travel time of a sample vehicle traveling straight through a sample fork in the road. The sample passable width of the sample road where the sample vehicle is located is the width threshold, and the moving speed of the sample obstacle on the sample road at the sample location is the speed threshold. The driving time of the sample is determined as the duration threshold.

[0102] In one embodiment, the determining module 401 is configured to: Determine the status of the oncoming vehicle's left turn signal and its parking position at the intersection; If the left turn signal is on and the parking position is within the preset area, the second driving route is determined to be a left turn at the intersection.

[0103] In one embodiment, the determining module 401 is configured to: Determine the status of the oncoming vehicle's left turn signal, its parking position, and the traffic flow corresponding to the target road. The target road intersects with the current road at a fork in the road and is located on the right side of the vehicle. If the left turn signal is on, the parking position is in the preset area, and the traffic flow is greater than the traffic flow threshold, the second driving route is determined to be a left turn at the intersection.

[0104] In one embodiment, a second processing module is further included, for: If the second driving path does not intersect with the first driving path at the intersection, or if the driving time is less than or equal to the time threshold, the braking control on the vehicle is released.

[0105] The vehicle control device provided in this application, employing the vehicle control method described in the above embodiments, can solve the technical problem of traffic congestion caused by straight-going vehicles potentially merging with oncoming vehicles at complex intersection conditions. Compared with the prior art, the beneficial effects of the vehicle control device provided in this application are the same as those of the vehicle control method provided in the above embodiments, and other technical features in the vehicle control device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0106] This application provides a vehicle control device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the vehicle control method in Embodiment 1 above.

[0107] The following is for reference. Figure 5 The diagram illustrates a structural schematic suitable for implementing vehicle control devices according to embodiments of this application. Vehicle control devices in embodiments of this application may include, but are not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 5The vehicle control device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of this application.

[0108] like Figure 5 As shown, the vehicle control device may include a processing unit 501 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage device 503 into a random access memory (RAM) 504. The RAM 504 also stores various programs and data required for the operation of the vehicle control device. The processing unit 501, ROM 502, and RAM 504 are interconnected via a bus 505. An input / output (I / O) interface 506 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 506: input devices 507 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 508 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 503 including, for example, magnetic tape, hard disk, etc.; and communication devices 509. Communication device 509 allows the vehicle control equipment to communicate wirelessly or wiredly with other devices to exchange data. Although the figures show vehicle control equipment with various systems, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0109] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 503, or installed from ROM 502. When the computer program is executed by processing device 501, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0110] The vehicle control device provided in this application, employing the vehicle control method described in the above embodiments, can solve the technical problem of traffic congestion caused by straight-going vehicles potentially merging with oncoming vehicles at complex intersections. Compared with the prior art, the beneficial effects of the vehicle control device provided in this application are the same as those of the vehicle control method provided in the above embodiments, and other technical features of this vehicle control device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0111] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0112] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0113] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the vehicle control method in the above embodiments.

[0114] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0115] The aforementioned computer-readable storage medium may be included in the vehicle control equipment; or it may exist independently and not be installed in the vehicle control equipment.

[0116] The aforementioned computer-readable storage medium carries one or more programs that, when executed by a vehicle control device, enable the vehicle control device to implement a vehicle control method.

[0117] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed 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 remote computers, the remote computer can 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 can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0118] 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 this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated 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, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0119] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0120] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described vehicle control method. This solves the technical problem of traffic congestion caused by the potential for straight-going vehicles to merge with oncoming vehicles at complex intersection conditions. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the vehicle control method provided in the above embodiments, and will not be repeated here.

[0121] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the vehicle control method described above.

[0122] The computer program product provided in this application can solve the technical problem of traffic congestion caused by the merging of straight-going vehicles with oncoming vehicles at complex intersections. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the vehicle control method provided in the above embodiments, and will not be repeated here.

[0123] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A vehicle control method, characterized in that, The vehicle control method includes: If there is a fork in the road ahead of the vehicle's current route, and the vehicle's first route is to go straight at the fork, determine the second route for the oncoming vehicle. When the second driving path intersects with the first driving path at the fork in the road, obtain scene information around the fork in the road; Based on the scenario information, predict the travel time for the vehicle to travel straight through the intersection; If the driving time exceeds a time threshold, the vehicle is controlled to stop before entering the fork in the road.

2. The method according to claim 1, characterized in that, The step of predicting the travel time of the vehicle traveling straight through the intersection based on the scenario information includes: Based on the scene information, determine the passable width of the current driving road and the status information of the obstacles on the current driving road; Based on the passable width and the status information corresponding to the obstacles, the travel time for the vehicle to pass straight through the intersection is predicted.

3. The method according to claim 2, characterized in that, After predicting the travel time of the vehicle traveling straight through the intersection based on the scenario information, the method further includes: Determine the sample travel time of a sample vehicle traveling straight through a sample fork in the road, wherein the sample passable width of the sample road where the sample vehicle is located is a width threshold, and the moving speed of the sample obstacle on the sample road at the sample location is a speed threshold. The driving time of the sample is determined as the duration threshold.

4. The method according to claim 1, characterized in that, Determining the second travel path corresponding to the oncoming vehicle includes: Determine the status of the left turn signal of the oncoming vehicle and its parking position at the intersection; If the left turn signal is on and the parking position is within the preset area, the second driving path is determined to be a left turn at the intersection.

5. The method according to claim 1, characterized in that, Determining the second travel path corresponding to the oncoming vehicle includes: Determine the left turn signal status, parking position, and traffic flow corresponding to the target road of the oncoming vehicle, wherein the target road intersects with the current driving road at the intersection and is located on the right side of the vehicle; If the left turn signal is on, the parking position is in a preset area, and the traffic flow is greater than the traffic flow threshold, the second driving path is determined to be a left turn at the intersection.

6. The method according to any one of claims 1-5, characterized in that, After bringing the vehicle to a stop before it enters the fork in the road, the process further includes: If the second driving path does not intersect with the first driving path at the fork in the road, or if the driving time is less than or equal to the time threshold, the braking control on the vehicle is released.

7. A vehicle control device, characterized in that, The vehicle control device includes: The determination module is used to determine the second driving path of the oncoming vehicle when there is a fork in the road ahead of the vehicle's current driving road and the vehicle's first driving path is to go straight at the fork in the road; The acquisition module is used to acquire scene information around the fork in the road when the second driving path intersects with the first driving path at the fork in the road. The prediction module is used to predict the travel time of the vehicle traveling straight through the intersection based on the scene information. The control module is used to control the vehicle to stop before entering the fork in the road if the driving time exceeds a time threshold.

8. A vehicle control device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the vehicle control method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the vehicle control method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the vehicle control method as described in any one of claims 1 to 6.

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