Vehicle control method and apparatus, storage medium, and electronic device
Patent Information
- Application Number
- AU2025244892
- Authority / Receiving Office
- AU · AU
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2024-03-27
- Filing Date
- 2025-03-04
- Publication Date
- 2026-09-17
Smart Images
Figure 00000000_0000_ABST
Abstract
Description
TECHNICAL FIELD The present disclosure relates to the technical fields of smart mines, autonomous driving, and unmanned vehicles, and in particular to a vehicle control method and apparatus, a storage medium, and an electronic device. BACKGROUND OF THE INVENTION In most unmanned task scenarios, there are usually a large number of autonomous driving vehicles executing tasks. The autonomous driving vehicles travel according to predicted travel trajectories of these vehicles to execute tasks of these vehicles. However, since these vehicles are unmanned, a deadlock situation (such as a head-on deadlock) inevitably occurs during the process of these vehicles executing the tasks. The deadlock situation affects the traffic efficiency of the vehicles and the timely execution of the tasks. SUMMARY OF THE INVENTION In view of this, the embodiments of the present disclosure provide a vehicle control method and apparatus, a storage medium, and an electronic device. According to a first aspect, some embodiments of the present disclosure provide a vehicle control method, including: in response to determining that a static obstacle has a travel conflict with a target vehicle, detecting whether vehicle-to-everything (V2X) information related to the static obstacle is received, to obtain a detection result, where the travel conflict indicates that the static obstacle is located on a predicted traveling trajectory of the target vehicle or in a region at a distance from the predicted traveling trajectory of the target vehicle that satisfies a specified distance condition, and the V2X information carries trajectory information; determining, based on the detection result, whether the static obstacle is a stationary vehicle; in response to determining that the static obstacle is the stationary vehicle, determining a conflict region corresponding to the target vehicle and the stationary vehicle, and determining a relationship between a predicted traveling direction of the target vehicle and a predicted traveling direction of the stationary vehicle in the conflict region; and determining, based on the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region, a travel strategy of the target vehicle, and controlling the target vehicle to travel according to the travel strategy. In combination with the first aspect, in some implementations of the first aspect, determining, based on the detection result, whether the static obstacle is the stationary vehicle includes: in response to the detection result indicating that the trajectory information related to the static obstacle is received, determining that the static obstacle is the stationary vehicle. In combination with the first aspect, in some implementations of the first aspect, detecting whether the V2X information related to the static obstacle is received to obtain the detection result in response to determining that the static obstacle has the travel conflict with the target vehicle includes: in response to determining that the static obstacle has the travel conflict with the target vehicle, starting to receive a broadcast message, and detecting whether the V2X information related to the static obstacle is included in the broadcast message, to obtain the detection result; or in response to determining that the static obstacle has the travel conflict with the target vehicle, parsing a historical broadcast message received within a specified time range to determine whether the V2X information related to the static obstacle is included in the historical broadcast message to obtain the detection result. In combination with the first aspect, in some implementations of the first aspect, determining the travel strategy of the target vehicle based on the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region includes: when the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region is an opposite direction relationship, determining a stop position of the target vehicle relative to the conflict region, and controlling the target vehicle to travel to the stop position to stop and wait, and to continue traveling after the stationary vehicle leaves the conflict region; optionally, the conflict region includes: a region where the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle intersect; optionally, when the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle intersect to obtain a plurality of intersection regions, an intersection region closest to the stationary vehicle is determined as the conflict region; or the conflict region is a region where the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle do not intersect but a distance between the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle satisfies the specified distance condition; optionally, both the target vehicle and the stationary vehicle are autonomous driving vehicles in a target scenario. In combination with the first aspect, in some implementations of the first aspect, determining the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region includes: determining a trajectory intersection angle of the predicted traveling trajectory of the target vehicle along a traveling direction of the target vehicle and the predicted traveling trajectory of the stationary vehicle along a traveling direction of the stationary vehicle; when the trajectory intersection angle is greater than a target angle, determining that the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region is an opposite direction relationship; and when the trajectory intersection angle is less than the target angle, determining that the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region is a same direction relationship; optionally, the target angle is less than 90 degrees, and further optionally, the target angle is greater than 85 degrees and less than 90 degrees. In combination with the first aspect, in some implementations of the first aspect, before detecting whether the V2X information related to the static obstacle is received in response to determining that the static obstacle has the travel conflict with the target vehicle, the vehicle control method further includes: in a process of traveling by the target vehicle based on the predicted traveling trajectory of the target vehicle, determining, based on environmental perception information within a target range acquired by the target vehicle, whether the static obstacle has the travel conflict with the target vehicle. In combination with the first aspect, in some implementations of the first aspect, the vehicle control method further includes: in response to the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region being a same direction relationship, controlling the target vehicle to continue traveling. According to a second aspect, some embodiments of the present application provide a vehicle control apparatus, including: a detection module, configured to, in response to determining that a static obstacle has a travel conflict with a target vehicle, detect whether vehicle-to-everything (V2X) information related to the static obstacle is received to obtain a detection result, where the travel conflict indicates that the static obstacle is located on a predicted traveling trajectory of the target vehicle or in a region at a distance from the predicted traveling trajectory of the target vehicle that satisfies a specified distance condition, and the V2X information carries trajectory information; a first determination module, configured to determine, based on the detection result, whether the static obstacle is a stationary vehicle; a second determination module, configured to, in response to determining that the static obstacle is the stationary vehicle, determine a conflict region corresponding to the target vehicle and the stationary vehicle, and determine a relationship between a predicted traveling direction of the target vehicle and a predicted traveling direction of the stationary vehicle in the conflict region; and a third determination module, configured to determine, based on the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region, a travel strategy of the target vehicle, and control the target vehicle to travel according to the travel strategy. According to a third aspect, some embodiments of the present disclosure provide a computer-readable storage medium storing a computer program, where the computer program is configured to execute the vehicle control method described in the first aspect. According to a fourth aspect, some embodiments of the present disclosure provide an electronic device, including: a processor; and a memory configured to store processor-executable instructions; where the processor is configured to execute the vehicle control method described in the first aspect. In the embodiments of the present disclosure, by means of the V2X information, it is possible to perceive in advance the static obstacle located on or in a nearby region of the predicted traveling trajectory of the target vehicle, facilitating the detection of potential travel conflicts at an earlier time point, thereby allowing the target vehicle more time to react and adjust the travel strategy of the target vehicle. Secondly, different types of obstacles have different impacts on the travel of the target vehicle. Based on the received V2X information, the embodiments of the present disclosure can accurately determine whether the static obstacle is the stationary vehicle that causes a potential deadlock, which helps to more accurately assess the risk of potential conflicts. After determining that the static obstacle is the stationary vehicle, the position of the conflict region between the stationary vehicle and the target vehicle is identified, and the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region is analyzed, thereby enabling more precise planning of the travel strategy of the target vehicle, including but not limited to deceleration and stopping to wait, and ensuring that the target vehicle can pass through the conflict region safely and efficiently, and reducing the risk of head-on collision with the stationary vehicle. BRIEF DESCRIPTION OF DRAWINGS The above and other objects, features, and advantages of the present disclosure will become more apparent from the following detailed description of the embodiments of the present disclosure with reference to the accompanying drawings. The accompanying drawings are used to provide a further understanding of the embodiments of the present disclosure, constitute a part of the specification, are used to explain the present disclosure together with the embodiments of the present disclosure, and do not constitute a limitation on the present disclosure. In the accompanying drawings, the same reference numerals generally represent the same components or steps. FIG. 1a is a schematic diagram of vehicle travel in an autonomous driving scenario according to some embodiments of the present disclosure. FIG. 1b is a schematic diagram of vehicle travel in an autonomous driving scenario according to other embodiments of the present disclosure. FIG. 2 is a schematic flowchart of a vehicle control method according to some embodiments of the present disclosure. FIG. 3 is a schematic flowchart of obtaining a detection result according to some embodiments of the present disclosure. FIG. 4 is a schematic flowchart of determining a travel strategy of a target vehicle according to some embodiments of the present disclosure. FIG. 5 is a schematic flowchart of determining a relationship between a predicted traveling direction of a target vehicle and a predicted traveling direction of a stationary vehicle according to some embodiments of the present disclosure. FIG. 6 is a structural schematic diagram of a vehicle control apparatus according to some embodiments of the present disclosure. FIG. 7 is a structural schematic diagram of an electronic device according to some embodiments of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION The technical solutions in the embodiments of the present disclosure will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present disclosure. Apparently, the described embodiments are some, rather than all, of the embodiments of the present disclosure. All other embodiments obtained by a person having ordinary skill in the art based on the embodiments in the present disclosure without making creative efforts shall fall within the protection scope of the present disclosure. In mine unmanned driving, operating positions of vehicles are changeable, and destinations of certain operation scenarios (such as crushing ports) are relatively fixed. For such areas, since the space is limited, a preset global trajectory is usually an optimal travel route. In these scenarios, the space for obstacle avoidance is limited, and excessive obstacle avoidance will reduce production efficiency. Therefore, it is expected that the vehicles can strictly follow the sequence and travel along the global trajectory. In the mine unmanned driving production environment, it is preferred to ensure that the vehicles pass sequentially by means of multivehicle yielding or stopping to wait, thereby improving the overall operation efficiency. FIG. 1a is a schematic diagram of vehicle travel in an autonomous driving scenario according to some embodiments of the present disclosure. As shown in FIG. 1a, a traveling trajectory of Vehicle A and a traveling trajectory of Vehicle B have an intersection point e. At this time, when Vehicle A and Vehicle B travel to the intersection point e simultaneously, a collision will occur, thereby affecting the normal travel of the vehicles. FIG. 1b is a schematic diagram of vehicle travel in an autonomous driving scenario according to other embodiments of the present disclosure. As shown in FIG. 1b, although a traveling trajectory of Vehicle C and a traveling trajectory of Vehicle D do not intersect, in this travel environment, a distance between the traveling trajectory of Vehicle C at point f and the traveling trajectory of Vehicle D at point g is relatively close, which also causes vehicle collision or deadlock. As to the problems occurring in FIG. 1a and FIG. 1b, although there is a yielding strategy between vehicles that can prevent mutual head-on blocking from resulting in a deadlock, the vehicles also stop in the deadlock region due to false detection or failure. When this situation occurs, other vehicles will stop and wait outside a specified distance according to the rules for handling static obstacles. This leads to a problem. When a faulty vehicle resumes normal functions or the false detection disappears, the vehicles that originally stopped to wait continue to remain stationary since the vehicles cannot independently determine that the obstacle has been cleared, making it impossible for both vehicles to continue traveling. Currently, there are mainly two strategies to avoid deadlocks between two agents. First, vehicle detour. As mentioned above, this method can effectively solve the problem when there is sufficient space or space for obstacle avoidance, but it is difficult to implement in environments with fixed routes and narrow spaces. Second, manual intervention. This method relies on human active observation to determine whether a faulty vehicle stays in the deadlock region for some reason, and issues instructions in real time to make vehicles traveling in the opposite direction stop outside the deadlock region. However, this method excessively relies on human attention and the real-time performance of instruction issuance, which increases the workload of dispatchers. Considering the particularity of mine scenarios, it is necessary to explore a new method suitable for avoiding deadlocks of multi-agents in open areas of mines, to ensure that multiple autonomous driving vehicles can operate efficiently and safely on fixed routes. To solve the above problems, according to some embodiments of the present disclosure, a vehicle control method is provided. The vehicle control method includes the following steps. A travel route of a host vehicle (namely target vehicle) is sent to other vehicles through Vehicle-to-Vehicle (V2V) communication technology, and it is determined whether there is a static vehicle of which a current position is on or near the travel route of the host vehicle, to determine whether there is a conflict between the host vehicle and the static vehicle. In response to determining that there is the conflict between the host vehicle and the static vehicle, a relationship between the traveling direction of the static vehicle and the traveling direction of the host vehicle is determined, and when the relationship between the direction of the host vehicle and the direction of the static vehicle satisfies a specified relationship condition, a conflict region is calculated through a V2V trajectory of the host vehicle and a V2V trajectory of the static vehicle, it is detected whether the host vehicle satisfies a static yielding condition, and in the affirmative case, the host vehicle is controlled to stop outside the conflict region to yield. Optionally, when two conflicts are found on the same trajectory based on the V2V trajectory of the host vehicle and the V2V trajectory of the static vehicle, the first conflict region is taken into account with respect to the stationary vehicle, and the second conflict region is ignored. Optionally, it is determined through perception or roadside device detection that there is a static obstacle having a travel conflict with the host vehicle, and then the V2V travel route sent by other vehicles is received to determine whether the static obstacle is a stationary vehicle. Taking a roadside device as an example, roadside devices installed at different road sections acquires at least one type of data such as video, images, and point clouds of the corresponding road sections, determines whether there is a static obstacle based on the data, and sends the determination result to the host vehicle. Alternatively, the data is also sent to the host vehicle, and the host vehicle processes the data to determine whether there is a static obstacle in the corresponding road section. Optionally, the roadside device that sends the data to the host vehicle is the roadside device whose distance from the host vehicle satisfies a specified condition. The specified condition includes that the distance between the roadside device and the host vehicle does not exceed a first specified distance; or the distance between the road section corresponding to the roadside device and the host vehicle does not exceed a second specified distance. The roadside device and the host vehicle communicates through Vehicle-to-Everything (V2X) technology, including V2V or Vehicle-to-Network (V2N) communication technology. Through this embodiment, the deadlock situation in the case of vehicles traveling in opposite directions in mine scenarios is avoided. FIG. 2 is a schematic flowchart of a vehicle control method according to some embodiments of the present disclosure. As shown in FIG. 2, the vehicle control method includes the following steps. In step S210, in response to determining that a static obstacle has a travel conflict with a target vehicle, it is detected whether V2X information related to the static obstacle is received, to obtain a detection result. Static obstacles refer to obstacles in a stationary state, including a stationary vehicle and a nonvehicle static obstacle. The non-vehicle static obstacle includes an object fixed on a road but causes an impact or potential danger to the travel of the target vehicle. Exemplarily, the nonvehicle static obstacle includes: a road facility, an underpass, a roadblock, a fixed camera, a rock, a hill, and the like. A travel conflict indicates that the static obstacle is located on the predicted traveling trajectory of the target vehicle, or is located in a region at a distance from the predicted traveling trajectory of the target vehicle that satisfies a specified distance condition. The predicted traveling trajectory is an expected travel path calculated based on a current state (such as a position, a speed, and a direction) of the target vehicle and future actions (such as acceleration, deceleration, and steering). The specified distance condition is a safety threshold used to determine which static obstacles pose potential risks to the travel of the target vehicle. The V2X information refers to information for interaction and communication between a vehicle and surrounding environment of this vehicle, other vehicles, and infrastructure. The V2X information in some embodiments further carries trajectory information. Through the trajectory information, the target vehicle determines the future movement of the stationary vehicle regarded as the static obstacle around the target vehicle, thereby more accurately determining whether there is a travel conflict. In step S220, it is determined, based on the detection result, whether the static obstacle is a stationary vehicle. In one example, it is first detected whether the V2X information related to the static obstacle having the travel conflict with the target vehicle is received. When the detection result indicates that the V2X information is received, key data such as an obstacle identifier, a position, and a type in the V2X information is further analyzed, thereby determining whether the static obstacle is the stationary vehicle. When the detection result indicates that the V2X information related to the static obstacle is not received, it indicates that the static obstacle is the non-vehicle static obstacle. In addition, the V2X information is lost or blocked during transmission. In this case, the type and state of the static obstacle are further determined based on a sensor (such as a radar or a camera). In another example, in a vehicle operation environment in a mine scenario, the possibility of a pedestrian moving in the environment is relatively small, and infrastructure in the environment is generally immovable. Therefore, when trajectory information related to the static obstacle is received, it is determined that the static obstacle is the stationary vehicle. In step S230, in response to determining that the static obstacle is the stationary vehicle, a conflict region corresponding to the target vehicle and the stationary vehicle is determined, and a relationship between a predicted traveling direction of the target vehicle and a predicted traveling direction of the stationary vehicle in the conflict region is determined. A conflict region refers to a region where there is a collision risk between the target vehicle and the stationary vehicle. Exemplarily, a method for determining the conflict region corresponding to the target vehicle and the stationary vehicle includes the following steps. The position of the target vehicle and the position of the stationary vehicle are determined. A minimum safety distance between the target vehicle and the stationary vehicle is calculated based on the position of the target vehicle and the position of the stationary vehicle. A circular region having the target vehicle as a centre and the minimum safety distance as a radius is determined as the conflict region. Alternatively, the predicted travel region of the stationary vehicle is determined based on the predicted trajectory of the stationary vehicle and bounding box information of the predicted trajectory of the stationary vehicle. A target travel region of the target vehicle is determined based on the predicted traveling trajectory of the target vehicle and vehicle travel safety parameters. The collision risk region, that is, the conflict region, is determined according to an intersection region between the predicted travel region and the target travel region. Optionally, an operation of determining the collision risk region according to the intersection region between the predicted travel region and the target travel region further include the following steps. The intersection region of the predicted travel region and the target travel region is determined. The intersection region is corrected according to sensor coordinates on a vehicle and vehicle coordinates to obtain a target collision risk region as the conflict region. Exemplarily, in the conflict region, the traveling direction of the target vehicle and the traveling direction of the stationary vehicle are predicted through a machine learning algorithm or a motion model based on a motion state and historical data of the target vehicle and the stationary vehicle. In one example, when a relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle is that there is an intersection or overlap, the collision risk in the conflict region is also relatively high. In this case, corresponding measures are also required to ensure safety. In step S240, a travel strategy of the target vehicle is determined based on the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region, and the target vehicle is controlled to travel according to the travel strategy. In one example, when there is no conflict relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle, the travel strategy of the target vehicle is to maintain a current travel state, and no special measures are required. The current travel state includes a current travel speed, a current travel direction, and a current traveling trajectory, and the like. In another example, although there is no direct conflict between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle, considering the current status of the current travel environment (such as poor visibility and a narrow road), the target vehicle still needs to decelerate or stop to yield. At this time, the travel strategy of the target vehicle is to gradually reduce the travel speed of the target vehicle until the target vehicle stops completely, to ensure that no collision or dangerous situation occurs when passing through the conflict region. It can be understood that the travel strategy of the target vehicle needs to be comprehensively considered and optimized in combination with the specific environment of a mine area, traffic rules, and the performance of an autonomous driving system. Meanwhile, to ensure the safety and reliability of travel, it is also necessary to conduct sufficient tests and verification on the autonomous driving system, and continuously collect feedback data during actual operation, so as to optimize and update the system. In the embodiments of the present disclosure, by means of the V2X information, it is possible to perceive in advance the static obstacle located on or in a nearby region of the predicted traveling trajectory of the target vehicle, facilitating the detection of potential travel conflicts at an earlier time point, thereby allowing the target vehicle more time to react and adjust the travel strategy of the target vehicle. Secondly, different types of obstacles have different impacts on the travel of the target vehicle. Based on the received V2X information, the embodiments of the present disclosure can accurately determine whether the static obstacle is the stationary vehicle that causes a potential deadlock, which helps to more accurately assess the risk of potential conflicts. After determining that the static obstacle is the stationary vehicle, the position of the conflict region between the stationary vehicle and the target vehicle is identified, and the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region is analyzed, thereby enabling more precise planning of the travel strategy of the target vehicle, including but not limited to deceleration and stopping to wait, and ensuring that the target vehicle can pass through the conflict region safely and efficiently, and reducing the risk of collision with the stationary vehicle. With reference to the embodiments shown in FIG. 2, in some other embodiments of the present disclosure, before step S210 is performed, the following steps are included. In a process of traveling by the target vehicle based on the predicted traveling trajectory of the target vehicle, it is determined, based on environmental perception information within a target range acquired by the target vehicle, whether the static obstacle has the travel conflict with the target vehicle. Specifically, the environmental perception information within the target range refers to key information such as positions, speeds, and directions of dynamic and static objects including roads, obstacles, other vehicles, and pedestrians within a certain range around the target vehicle. These information can help the target vehicle understand the current travel environment, thereby making correct decisions and planning a safe traveling trajectory. Exemplarily, the target vehicle acquires the environmental perception information within the target range through sensor technologies and perception algorithms. Regarding the sensor technologies, the target vehicle is equipped with various sensors, such as a lidar, a camera, and a millimeter-wave radar, which can scan the surrounding environment in real time and collect a large amount of data. For example, the lidar accurately acquires the distance and position of a target object by emitting a laser beam and measuring the time for the laser beam to be reflected back. The camera captures images of roads and obstacles to provide rich visual information for the autonomous driving system. Regarding the perception algorithms, the perception algorithms process and analyze raw data collected by the sensors to extract useful information. For example, a target detection and recognition algorithm can analyze and recognize surrounding vehicles, pedestrians, and other obstacles. A target tracking algorithm can estimate and predict motion trajectories of these objects. An environment modeling algorithm can construct an environment model around the vehicle based on the perceived information, providing a basis for decision-making and planning. In some embodiments, through perceiving the static obstacles within the target range in real time, the target vehicle identifies potential travel conflicts, thereby adjusting the traveling trajectory of the target vehicle to avoid collisions with these static obstacles and improving the safety of road travel. Through continuously collecting and analyzing the environmental perception information, the capability of the target vehicle to identify and cope with various static obstacles is also gradually improved, so that the autonomous driving system of the target vehicle can maintain stable performance in various complex environments. FIG. 3 is a schematic flowchart of obtaining a detection result according to some embodiments of the present disclosure. The embodiments shown in FIG. 3 are extended based on the embodiments shown in FIG. 2. The following focuses on the differences between the embodiments shown in FIG. 3 and the embodiments shown in FIG. 2, and the same parts will not be repeated. As shown in FIG. 3, in some implementations, an operation of detecting whether the V2X information related to the static obstacle is received to obtain the detection result in response to determining that the static obstacle has the travel conflict with the target vehicle includes the following steps. In step S310, in response to determining that the static obstacle has the travel conflict with the target vehicle, reception of a broadcast message is started, and it is detected whether the broadcast message includes the V2X information related to the static obstacle, to obtain the detection result. In the field of V2X communication, the broadcast message refers to information transmitted to relevant receivers among vehicles, road infrastructure, and other traffic participants through wireless communication technology. The broadcast message includes traffic conditions, road safety warnings, vehicle states, and the like. Thus, through the broadcast message, the target vehicle acquires dynamic information of a surrounding environment in real time, including positions, speeds, and traveling directions of other vehicles. After it is determined that the static obstacle has the travel conflict with the target vehicle, the broadcast message is received and the V2X information related to the static obstacle is detected from the broadcast message, thereby helping the target vehicle respond in a timely manner to avoid potential collision risks. In one example, a method for detecting whether the V2X information related to the static obstacle is included in the broadcast message includes the following steps. First, the broadcast message is parsed. After the broadcast message is parsed, information related to the static obstacle is filtered out based on predefined message types and identifiers. For example, a specific field or tag is set to identify the information related to the static obstacle. Through checking these fields or tags, a relevant data segment is quickly located. Further, received attributes such as a position and a type are matched and identified with known static obstacles in a database. When a match is found, it is confirmed that the information is the V2X information related to the static obstacle. In step S320, in response to determining that the static obstacle has the travel conflict with the target vehicle, a historical broadcast message received within a specified time range is parsed to determine whether the V2X information related to the static obstacle is included in the historical broadcast message to obtain the detection result. The historical broadcast messages received within the specified range refer to historical records of the broadcast messages sent by other vehicles or road infrastructure and received by the target vehicle within a certain time span. Similarly, these broadcast messages also include various traffic-related information, such as vehicle positions, speeds, and traveling directions. Generally, static obstacles of non-vehicle types (i.e., non-vehicle static obstacles) do not transmit the V2X information, but other vehicles or infrastructure detect these obstacles and transmit related information. Therefore, through parsing the historical broadcast messages received within the specified time range and searching for information related to static obstacles included in the historical broadcast messages, it is determined whether the static obstacle has the travel conflict with the target vehicle, thereby making corresponding driving decisions or warning prompts. In one example, a method for analyzing static obstacle information in the historical broadcast messages include the following steps. First, the historical broadcast messages within a specified time range are collected, where these historical broadcast messages come from other vehicles, roadside units, or traffic management systems. The collected data is preprocessed to ensure data quality and consistency. The content of the broadcast messages is parsed to extract information related to static obstacles, including positions, sizes, types (such as buildings, trees, and traffic facilities), and static attributes of the obstacles, timestamps, sender identities, and signal strengths. Pattern recognition or machine learning algorithms are used to analyze features in the historical broadcast messages to identify the static obstacles. For known types of static obstacles, predefined models or rules are used for matching and identification; and for unknown types of obstacles, unsupervised learning methods are used for clustering or anomaly detection. It is understood that step S310 and step S320 are two parallel schemes for determining the detection result. Step S310 describes that after the static obstacle is perceived, the detection of the broadcast messages is started to obtain the detection result. Step S320 describes that during the travel of a vehicle, V2X communication is performed in real time, that is, other vehicles communicate with the target vehicle in real time through V2X. Subsequently, a perception system of the target vehicle determines the static obstacle. In this case, the detection result is obtained based on the previously received historical broadcast messages. For step S320, especially in cases of curves or other obstacles causing occlusion that affect the perception and recognition of the target vehicle, the accuracy of the detection result can be improved. In step S310, after determining that the static obstacle has the travel conflict with the target vehicle, reception of the broadcast message is started and it is detected in real time whether the broadcast message includes the V2X information related to the static obstacle. An advantage of this method is strong real-time performance. Once a broadcast message including static obstacle information is received, the target vehicle can respond immediately, such as through adjusting a traveling trajectory or speed, thereby avoiding a collision with the static obstacle. The implementation method of step S320 focuses more on the comprehensiveness of information and the utilization of historical data. By analyzing the historical data, the target vehicle can learn more details such as the position, size, and existence duration of the static obstacle, which is very helpful for the vehicle to make more accurate decisions. The above two methods can complement each other to provide more comprehensive and accurate information. Real-time detection can ensure timely response of the target vehicle to the static obstacle, while historical data parsing can provide more detailed and in-depth information for the vehicle, helping the target vehicle make more accurate decisions, and significantly improving the safety and stability of vehicle travel. FIG. 4 is a schematic flowchart of determining a travel strategy of a target vehicle according to some embodiments of the present disclosure. The embodiments shown in FIG. 4 are extended based on the embodiments shown in FIG. 2. The following focuses on the differences between the embodiments shown in FIG. 4 and the embodiments shown in FIG. 2, and the same parts will not be repeated. As shown in FIG. 4, in some implementations, an operation of determining the travel strategy of the target vehicle based on the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region includes the following steps. In step S410, the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region is determined. The conflict region includes: a region where the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle intersect. When there are a plurality of intersecting regions of the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle, an intersecting region closest to the stationary vehicle is determined as the conflict region; or, a region where the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle do not intersect, but a distance between the two trajectories satisfies a specified distance condition. Specifically, when the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle intersect, it means that the target vehicle and the stationary vehicle meet at a certain time point or a certain location in the future. In this case, the intersecting region is regarded as the conflict region. When there are the plurality of intersecting regions, the closer to the stationary vehicle, the greater the potential collision risk. Therefore, the intersecting region closest to the stationary vehicle is determined as the conflict region. In addition, sometimes although the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle do not intersect, the distance between the two trajectories is close enough (that is, the specified distance condition is satisfied), which also leads to a collision in the event of a sudden situation or an operation error. Therefore, this region is also determined as the conflict region. Both the target vehicle and the stationary vehicle are autonomous driving vehicles in a target scenario. Exemplarily, the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle includes a same direction relationship, an opposite direction relationship, an intersecting relationship, and a perpendicular relationship, and the like. Generally, the same direction relationship means that the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle are substantially the same or similar. The opposite direction relationship means that the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle are completely opposite. The intersecting relationship means that the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle form an intersection. At this time, the target vehicle needs to pass through a direction where the stationary vehicle is located. The perpendicular relationship means that the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle are perpendicular, and at this time, the target vehicle needs to turn or go straight through an intersection or a road where the stationary vehicle is located. In an actual situation, when the determination result of step S410 is the opposite direction relationship, step S420 is performed. When the determination result of step S410 is the same direction relationship, step S430 is performed. In step S420, a stop position of the target vehicle relative to the conflict region is determined, and the target vehicle is controlled to travel to the stop position to stop and wait, and to continue traveling after the stationary vehicle leaves the conflict region. A stopping position refers to a safe position outside the conflict region where the target vehicle stops and waits, so as to avoid a collision with the stationary vehicle while not hindering the normal travel of other vehicles. Exemplarily, when determining the stopping position, factors such as a size of the conflict region, a size and maneuverability of the target vehicle, road conditions and traffic conditions, and a position and a state of the stationary vehicle are considered. Specifically, the size of the conflict region determines how far the target vehicle needs to be from the stationary vehicle to ensure safety. Different vehicle sizes and maneuverability affect the required safe stopping distance. A road width, a curvature, a traffic flow, and the like affect the selection of the stopping position. In addition, a specific position of the stationary vehicle and whether the stationary vehicle moves at any time are also factors to be considered when determining the stopping position. Exemplarily, the stopping position is a position at a distance of 10 meters to 30 meters from the conflict region. Once the stopping position is determined, the target vehicle is controlled to travel to the stopping position and safely stop to wait. During the stopping and waiting, the target vehicle turns on a hazard warning and the like to remind other road users. In step S430, the target vehicle is controlled to continue traveling. Since the traveling direction of the target vehicle and the traveling direction of the stationary vehicle are the same, the target vehicle and the stationary vehicle do not travel directly toward each other, and thus there is no direct collision risk. In this case, when the target vehicle stops or decelerates, the target vehicle causes unnecessary traffic congestion or interfere with other vehicles traveling normally. Therefore, the target vehicle safely continues to travel according to the predicted traveling direction of the target vehicle. However, the target vehicle still needs to remain alert to the surrounding environment and be ready to deal with possible emergencies at any time, such as the stationary vehicle suddenly starting or changing lanes. In addition, when the travel speed of the target vehicle is too fast or the distance to the stationary vehicle is too close, the target vehicle also needs to appropriately decelerate or adjust the traveling trajectory to ensure safety. In some embodiments, when the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle have the opposite direction relationship, the potential collision risk between the target vehicle and the stationary vehicle is effectively avoided by determining the stopping position and controlling the target vehicle to stop and wait at the stopping position. This strategy reduces the probability of traffic accidents and improves the travel safety. During the period when the target vehicle stops and waits, the stationary vehicle has an opportunity to leave the conflict region. Once the stationary vehicle leaves, the target vehicle continues to travel, thereby avoiding traffic congestion caused by the target vehicle and the stationary vehicle facing each other. When facing the stationary vehicle traveling in the opposite direction, through determining the stopping position and controlling the target vehicle to stop and wait, the target vehicle deals with complex traffic situations more calmly. When the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle do not intersect, but the distance between the two trajectories satisfies the specified distance condition, it means that potential risks are identified in advance and corresponding preventive measures are taken even in some seemingly non-conflict situations. This helps to reduce emergency braking or lane changing caused by emergencies, thereby improving the overall travel efficiency. FIG. 5 is a schematic flowchart of determining a relationship between a predicted traveling direction of a target vehicle and a predicted traveling direction of a stationary vehicle according to some embodiments of the present disclosure. The embodiments shown in FIG. 5 are extended based on the embodiments shown in FIG. 2. The following focuses on the differences between the embodiments shown in FIG. 5 and the embodiments shown in FIG. 2, and the same parts will not be repeated. As shown in FIG. 5, in some implementations, an operation of determining the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region includes the following steps. In step S510, a trajectory intersection angle of the predicted traveling trajectory of the target vehicle along a traveling direction of the target vehicle and the predicted traveling trajectory of the stationary vehicle along a traveling direction of the stationary vehicle is determined. Exemplarily, current positions, speeds, directions, and other motion data of the target vehicle and the stationary vehicle are acquired through sensors and a Global Positioning System (GPS) of each vehicle. Based on the vehicle motion data, a kinematics model or a machine learning algorithm is used to predict a traveling trajectory of the vehicle in a future time period. Through comparing the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle, it is determined whether the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle will intersect in the future. When the predicted travel trajectories intersect, a specific trajectory intersection point needs to be calculated. Once the trajectory intersection point is determined, an included angle between the traveling direction of the target vehicle and the traveling direction of the stationary vehicle at the intersection point is calculated, and this included angle is the trajectory intersection angle. Generally, the trajectory intersection angle is obtained by calculating an included angle between two straight lines, where the two straight lines respectively represent the traveling direction of the target vehicle and the traveling direction of the stationary vehicle at the intersection point. It should be noted that since vehicle motion is affected by various factors (such as road surface conditions, driver operations, wind speed, and the like), there will be certain errors and uncertainties in the predicted travel trajectories and the intersection angles. Therefore, in practical applications, methods such as probability models or fuzzy logic are used to handle these uncertainties. In step S520, a magnitude relationship between the trajectory intersection angle and a target angle is determined. Specifically, the selection of the target angle needs to comprehensively consider factors such as road conditions and vehicle speeds to ensure traffic safety and travel efficiency. Generally, the setting of the target angle should be able to distinguish obvious opposite direction and same direction travel situations. Exemplarily, the target angle is less than 90 degrees. Further optionally, the target angle is greater than 85 degrees and less than 90 degrees. In an actual situation, when the determination result of step S520 is that the trajectory intersection angle is greater than the target angle, step S530 is performed. When the determination result of step S520 is that the trajectory intersection angle is less than the target angle, step S540 is performed. In step S530, it is determined that the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region is an opposite direction relationship. Specifically, when the trajectory intersection angle is greater than the target angle, it means that there is a relatively large difference between the traveling direction of the target vehicle and the traveling direction of the stationary vehicle, and there is an obvious tendency of traveling toward each other. In this case, the two vehicles have a direct conflict during future travel. Therefore, it is necessary to determine that there is the opposite direction relationship, so as to take corresponding safety measures, such as stopping and waiting, or decelerating to yield. In step S540, it is determined that the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region is a same direction relationship. When the trajectory intersection angle is less than the target angle, the difference between the traveling direction of the target vehicle and the traveling direction of the stationary vehicle is relatively small, and the target vehicle and the stationary vehicle are considered to be traveling in the same direction. In this case, the two vehicles are unlikely to have a direct conflict during future travel. Therefore, it is determined that there is the same direction relationship, and the target vehicle is allowed to continue traveling. In some embodiments, through accurately calculating the trajectory intersection angle, the relationship between the traveling direction of the target vehicle and the traveling direction of the stationary vehicle are accurately determined. When the opposite direction relationship is determined, preventive measures are taken in a timely manner, such as decelerating, yielding, or stopping and waiting, thereby avoiding potential collision risks and significantly improving driving safety. When the same direction relationship is determined, it means that the traveling direction of the target vehicle and the traveling direction of the stationary vehicle are substantially the same. In this case, the target vehicle continues traveling without taking additional yielding measures, thereby maintaining the smoothness of traffic and reducing unnecessary traffic congestion. Adopting this determination basis helps to optimize traffic flow, reduce the occurrence of traffic accidents, and improve the overall traffic management efficiency. The embodiments of the vehicle control method of the present disclosure are described in detail above with reference to FIG. 2 to FIG. 5. The following describes the embodiments of a vehicle control apparatus of the present disclosure in detail with reference to FIG. 6. It should be understood that the description of the embodiments of the vehicle control method corresponds to the description of the embodiments of the vehicle control apparatus. Therefore, for the parts that are not described in detail, reference is made to the method embodiments. FIG. 6 is a structural schematic diagram of a vehicle control apparatus according to some embodiments of the present disclosure. As shown in FIG. 6, the vehicle control apparatus 60 according to some embodiments of the present disclosure includes: a detection module 610, configured to, in response to determining that a static obstacle has a travel conflict with a target vehicle, detect whether V2X information related to the static obstacle is received to obtain a detection result, where the travel conflict indicates that the static obstacle is located on a predicted traveling trajectory of the target vehicle or in a region at a distance from the predicted traveling trajectory of the target vehicle that satisfies a specified distance condition, and the V2X information carries trajectory information; a first determination module 620, configured to determine, based on the detection result, whether the static obstacle is a stationary vehicle; a second determination module 630, configured to, in response to determining that the static obstacle is the stationary vehicle, determine a conflict region corresponding to the target vehicle and the stationary vehicle, and determine a relationship between a predicted traveling direction of the target vehicle and a predicted traveling direction of the stationary vehicle in the conflict region; and a third determination module 640, configured to determine, based on the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region, a travel strategy of the target vehicle, and control the target vehicle to travel according to the travel strategy. In some embodiments, the first determination module 620 is further configured to, in response to the detection result indicating that the trajectory information related to the static obstacle is received, determine that the static obstacle is the stationary vehicle. In some embodiments, the detection module 610 is further configured to, in response to determining that the static obstacle has the travel conflict with the target vehicle, start to receive a broadcast message, and detect whether the V2X information related to the static obstacle is included in the broadcast message, to obtain the detection result; or in response to determining that the static obstacle has the travel conflict with the target vehicle, parse a historical broadcast message received within a specified time range to determine whether the V2X information related to the static obstacle is included in the historical broadcast message to obtain the detection result. In some embodiments, the third determination module 640 is further configured to, when the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region is an opposite direction relationship, determine a stop position of the target vehicle relative to the conflict region, and control the target vehicle to travel to the stop position to stop and wait, and to continue traveling after the stationary vehicle leaves the conflict region; optionally, the conflict region includes: a region where the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle intersect; optionally, when the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle intersect to obtain a plurality of intersection regions, an intersection region closest to the stationary vehicle is determined as the conflict region; or the conflict region is a region where the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle do not intersect but a distance between the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle satisfies the specified distance condition. In some embodiments, the second determination module 630 is further configured to determine a trajectory intersection angle of the predicted traveling trajectory of the target vehicle along a traveling direction of the target vehicle and the predicted traveling trajectory of the stationary vehicle along a traveling direction of the stationary vehicle; when the trajectory intersection angle is greater than a target angle, determine that the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region is an opposite direction relationship; and when the trajectory intersection angle is less than the target angle, determine that the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region is a same direction relationship; optionally, the target angle is less than 90 degrees, and further optionally, the target angle is greater than 85 degrees and less than 90 degrees. In some embodiments, the detection module 610 is further configured to, in a process of traveling by the target vehicle based on the predicted traveling trajectory of the target vehicle, determine whether the static obstacle has the travel conflict with the target vehicle based on environmental perception information within a target range acquired by the target vehicle. In some embodiments, the third determination module 630 is further configured to, in response to the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region being a same direction relationship, control the target vehicle to continue traveling. Next, an electronic device according to some embodiments of the present disclosure is described with reference to FIG. 7. FIG. 7 is a structural schematic diagram of an electronic device according to some exemplary embodiments of the present disclosure. As shown in FIG. 7, the electronic device 70 includes one or more processors 701 and a memory 702. The processor 701 is a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and controls other components in the electronic device 70 to perform desired functions. The memory 702 includes one or more computer program products, and the computer program products include various forms of computer-readable storage media, such as transitory memories and / or non-transitory memories. The transitory memory includes, for example, a random access memory (RAM) and / or a cache memory (cache). The non-transitory memory includes, for example, a read-only memory (ROM), a hard disk, a flash memory, and the like. One or more computer program instructions are stored on the computer-readable storage medium, and the processor 701 runs the program instructions to implement the vehicle control method of the various embodiments of the present disclosure described above and / or other desired functions. Various contents such as a predicted traveling trajectory of a target vehicle, V2X information of a static obstacle, a detection result, and a travel strategy of the target vehicle is also stored in the computer-readable storage medium. In one example, the electronic device 70 further includes: an input device 703 and an output device 704, and these components are interconnected through a bus system and / or other forms of connection mechanisms (not shown). The input device 703 includes, for example, a keyboard, a mouse, and the like. The output device 704 outputs various information to the outside, including the predicted traveling trajectory of the target vehicle, the V2X information of the static obstacle, the detection result, the travel strategy of the target vehicle, and the like. The output device 704 includes, for example, a display, a speaker, a printer, a communication network and remote output devices connected thereto, and the like. Certainly, for the sake of simplicity, FIG. 7 shows some of the components in the electronic device 70 related to the present disclosure, and components such as a bus, an input / output interface, and the like are omitted. In addition, according to specific application conditions, the electronic device 70 further includes any other appropriate components. In addition to the above methods and devices, the embodiments of the present disclosure further provide a computer program product including computer program instructions, where the computer program instructions, when run by a processor, cause the processor to perform the steps in the vehicle control method according to the various embodiments of the present disclosure described above in the present disclosure. The computer program product is written in any combination of one or more programming languages for program codes for performing the operations of the embodiments of the present disclosure, and the programming languages include object-oriented programming languages, such as Java, C++, and the like, and also include conventional procedural programming languages, such as the “C” language or similar programming languages. The program codes are executed entirely on a user computing device, partially on a user device, executed as a stand-alone software package, partially on a user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In addition, the embodiments of the present disclosure further provide a computer-readable storage medium storing computer program instructions, where the computer program instructions, when run by a processor, cause the processor to perform the steps in the vehicle control method according to the various embodiments of the present disclosure described above in the present disclosure. The computer-readable storage medium adopts any combination of one or more readable media. The readable medium is a readable signal medium or a readable storage medium. The readable storage medium includes, for example but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk readonly memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. The basic principles of the present disclosure have been described above in combination with specific embodiments. However, it should be pointed out that the advantages, benefits, effects, and the like mentioned in the present disclosure are examples and not limitations, and it should not be considered that these advantages, benefits, effects, and the like are necessary for the various embodiments of the present disclosure. In addition, the specific details disclosed above are for the purpose of illustration and ease of understanding, and are not limitations. The above details do not limit the present disclosure to be implemented by adopting the above specific details. The block diagrams of components, apparatuses, devices, and systems involved in the present disclosure are illustrative examples and are not intended to require or imply that the connections, arrangements, and configurations are made in the manner shown in the block diagrams. As will be appreciated by a person having ordinary skill in the art, these components, apparatuses, devices, and systems are connected, arranged, and configured in any manner. Words such as “including”, “containing”, “having”, and the like are open-ended terms, meaning “including but not limited to”, and are used interchangeably therewith. The words “or” and “and” used herein mean the word “and / or”, and are used interchangeably therewith, unless the context clearly indicates otherwise. The word “such as” used herein means the phrase “such as but not limited to”, and are used interchangeably therewith. It should also be pointed out that in the apparatuses, devices, and methods of the present disclosure, the respective components or steps are decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent solutions of the present disclosure. The above descriptions of the disclosed aspects are provided to enable a person having ordinary skill in the art to make or use the present disclosure. Various modifications to these aspects are readily apparent to a person having ordinary skill in the art, and the general principles defined herein are applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein. The above descriptions have been given for the purpose of illustration and description. Furthermore, the descriptions are not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although several exemplary aspects and embodiments have been discussed above, a person having ordinary skill in the art will recognize certain variations, modifications, changes, additions, and sub-combinations thereof.
Claims
1. A vehicle control method, comprising:in response to determining that a static obstacle has a travel conflict with a target vehicle, detecting whether vehicle-to-everything (V2X) information related to the static obstacle is received, to obtain a detection result, wherein the travel conflict indicates that the static obstacle is located on a predicted traveling trajectory of the target vehicle or in a region at a distance from the predicted traveling trajectory of the target vehicle that satisfies a specified distance condition, and the V2X information carries trajectory information;determining, based on the detection result, whether the static obstacle is a stationary vehicle;in response to determining that the static obstacle is the stationary vehicle, determining a conflict region corresponding to the target vehicle and the stationary vehicle, and determining a relationship between a predicted traveling direction of the target vehicle and a predicted traveling direction of the stationary vehicle in the conflict region; and determining, based on the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region, a travel strategy of the target vehicle, and controlling the target vehicle to travel according to the travel strategy.
2. The vehicle control method according to claim 1, wherein determining, based on the detection result, whether the static obstacle is the stationary vehicle comprises:in response to the detection result indicating that the trajectory information related to the static obstacle is received, determining that the static obstacle is the stationary vehicle.
3. The vehicle control method according to claim 1, wherein detecting whether the V2X information related to the static obstacle is received to obtain the detection result in response to determining that the static obstacle has the travel conflict with the target vehicle comprises:in response to determining that the static obstacle has the travel conflict with the target vehicle, starting to receive a broadcast message, and detecting whether the V2X informationrelated to the static obstacle is comprised in the broadcast message, to obtain the detection result; orin response to determining that the static obstacle has the travel conflict with the target vehicle, parsing a historical broadcast message received within a specified time range to determine whether the V2X information related to the static obstacle is comprised in the historical broadcast message to obtain the detection result.
4. The vehicle control method according to any one of claims 1 to 3, wherein determining the travel strategy of the target vehicle based on the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region comprises:when the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region is an opposite direction relationship, determining a stop position of the target vehicle relative to the conflict region, and controlling the target vehicle to travel to the stop position to stop and wait, and to continue traveling after the stationary vehicle leaves the conflict region;optionally, the conflict region comprises: a region where the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle intersect; optionally, when the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle intersect to obtain a plurality of intersection regions, an intersection region closest to the stationary vehicle is determined as the conflict region; or the conflict region is a region where the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle do not intersect but a distance between the predicted traveling trajectory of the target vehicle and the predicted traveling trajectory of the stationary vehicle satisfies the specified distance condition;optionally, both the target vehicle and the stationary vehicle are autonomous driving vehicles in a target scenario.
5. The vehicle control method according to any one of claims 1 to 4, wherein determining the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region comprises:determining a trajectory intersection angle of the predicted traveling trajectory of the target vehicle along a traveling direction of the target vehicle and the predicted traveling trajectory of the stationary vehicle along a traveling direction of the stationary vehicle;when the trajectory intersection angle is greater than a target angle, determining that the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region is an opposite direction relationship; andwhen the trajectory intersection angle is less than the target angle, determining that the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region is a same direction relationship;optionally, the target angle is less than 90 degrees, and further optionally, the target angle is greater than 85 degrees and less than 90 degrees.
6. The vehicle control method according to any one of claims 1 to 5, before detecting whether the V2X information related to the static obstacle is received in response to determining that the static obstacle has the travel conflict with the target vehicle, further comprising: in a process of traveling by the target vehicle based on the predicted traveling trajectory of the target vehicle, determining, based on environmental perception information within a target range acquired by the target vehicle, whether the static obstacle has the travel conflict with the target vehicle.
7. The vehicle control method according to any one of claims 1 to 6, further comprising: in response to the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region being a same direction relationship, controlling the target vehicle to continue traveling.
8. A vehicle control apparatus, comprising:a detection module, configured to, in response to determining that a static obstacle has a travel conflict with a target vehicle, detect whether vehicle-to-everything (V2X) information related to the static obstacle is received to obtain a detection result, wherein thetravel conflict indicates that the static obstacle is located on a predicted traveling trajectory of the target vehicle or in a region at a distance from the predicted traveling trajectory of the target vehicle that satisfies a specified distance condition, and the V2X information carries trajectory information;a first determination module, configured to determine, based on the detection result, whether the static obstacle is a stationary vehicle;a second determination module, configured to, in response to determining that the static obstacle is the stationary vehicle, determine a conflict region corresponding to the target vehicle and the stationary vehicle, and determine a relationship between a predicted traveling direction of the target vehicle and a predicted traveling direction of the stationary vehicle in the conflict region; anda third determination module, configured to determine, based on the relationship between the predicted traveling direction of the target vehicle and the predicted traveling direction of the stationary vehicle in the conflict region, a travel strategy of the target vehicle, and control the target vehicle to travel according to the travel strategy.
9. A computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the vehicle control method as claimed in any one of claims 1 to 7.
10. An electronic device, comprising:a processor; anda memory configured to store processor-executable instructions;wherein the processor is configured to execute the vehicle control method as claimed in any one of claims 1 to 7.