Vehicle control method and device and vehicle

Abstract

The invention relates to a vehicle control method and device and a vehicle, and the method comprises the steps: responding to a situation that a mobile terminal of a user satisfies an unlocking triggering condition of a target vehicle, obtaining a motion track of the mobile terminal, and triggering the target vehicle to execute a welcome operation, the triggering basis of the welcome operation comprising the motion track. According to the method, the unlocking triggering condition is combined with the motion trail analysis of the mobile terminal, so that the situation that the welcome operation is triggered by mistake only when the user approaches the vehicle is avoided, and the user experience and the safety of the vehicle are improved.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and more specifically, to methods, devices, and vehicles for vehicle control. Background Technology

[0002] Current smart car welcome functions primarily rely on near-field communication (NFC) technology or single biometric identification methods. These solutions face challenges in practical applications. When a user briefly lingers near a vehicle while carrying a mobile device—for example, walking around a parking lot to check the vehicle's condition or conversing with others near the car—the system may misinterpret this as an intention to get in, leading to accidental unlocking of the doors or unexplained activation of welcome lights. This not only disrupts the user's normal activities but may also pose safety hazards such as rainwater seepage in inclement weather. In complex environments, such as busy shopping mall parking lots, users may linger near their vehicles for extended periods, organizing belongings or waiting for companions. However, the system cannot effectively distinguish between this approach without the intention to get in and genuine preparation to board, thus incorrectly triggering unlocking operations and posing risks of privacy breaches or property loss. Summary of the Invention

[0003] The purpose of this disclosure is to provide a method, apparatus, and vehicle for vehicle control.

[0004] To achieve the above objectives, according to a first aspect of this disclosure, a method for vehicle control is provided, the method comprising:

[0005] In response to the user's mobile terminal meeting the unlocking trigger condition of the target vehicle, the movement trajectory of the mobile terminal is acquired; the mobile terminal is used to unlock the target vehicle. The target vehicle is triggered to perform a welcoming operation, wherein the triggering basis for the welcoming operation includes the movement trajectory.

[0006] Optionally, triggering the target vehicle to perform a welcoming operation includes: When the motion trajectory meets the preset welcoming conditions, the target vehicle is triggered to perform a welcoming operation.

[0007] Optionally, the preset welcoming conditions include one or more of the following conditions: The motion trajectory indicates that the mobile terminal is in a preset recognition area, which is a pre-set area based on the position of the door handle of the target vehicle door; The motion trajectory indicates that the time the mobile terminal is in the preset recognition area is greater than or equal to a preset time threshold. The motion trajectory indicates that the user is approaching the target vehicle and that the user is in a deceleration state; The motion trajectory indicates that the radial velocity of the mobile terminal is less than or equal to a preset speed threshold.

[0008] Optionally, obtaining the motion trajectory of the mobile terminal includes: The location information of the mobile terminal is obtained through the ultra-wideband (UWB) communication module of the target vehicle; The first point cloud data of multiple objects around the target vehicle are obtained by the lidar of the target vehicle; Based on the location information and the first point cloud data, the target point cloud data corresponding to the mobile terminal is determined; The motion trajectory is obtained based on the target point cloud data.

[0009] Optionally, determining the target point cloud data corresponding to the mobile terminal based on the location information and the first point cloud data includes: Cluster the first point cloud data of the multiple objects to obtain multiple clusters; Based on the location information, the target cluster corresponding to the mobile terminal is determined from the plurality of clusters; The point cloud data in the target cluster is used as the target point cloud data.

[0010] Optionally, determining the target cluster corresponding to the mobile terminal from the plurality of clusters based on the location information includes: Based on the location information, the confidence level corresponding to each cluster is obtained, and the confidence level represents the degree of confidence that the cluster is the target cluster; The cluster with the highest confidence level is selected as the target cluster.

[0011] Optionally, the unlocking trigger condition includes: The user is authenticated; and / or, The distance between the mobile terminal and the target vehicle is less than or equal to a first preset distance threshold.

[0012] Optionally, the welcoming operation includes one or more of the following: Control the illumination of welcome lights and / or floor projection lights; Unlock the vehicle; Unlock the vehicle and open the door in the vehicle that is closest to the mobile terminal at a preset angle.

[0013] According to a second aspect of this disclosure, an electronic device is provided, comprising: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method described in the first aspect.

[0014] According to a third aspect of this disclosure, a vehicle is provided that includes the electronic equipment described in the second aspect.

[0015] The above technical solution, in response to the user's mobile terminal meeting the unlock trigger conditions of the target vehicle, acquires the movement trajectory of the mobile terminal and triggers the target vehicle to perform a welcoming operation. The triggering basis for the welcoming operation includes the movement trajectory. By combining the unlock trigger conditions with the analysis of the mobile terminal's movement trajectory, the system avoids the situation where the welcoming operation is mistakenly triggered simply because the user is near the vehicle, thereby improving user experience and vehicle safety.

[0016] Other features and advantages of this disclosure will be described in detail in the following detailed description section. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate the present disclosure and form part of the specification. They are used together with the following detailed description to explain the present disclosure, but do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart illustrating a vehicle control method according to an exemplary embodiment; Figure 2 This is a flowchart illustrating a vehicle control method according to an exemplary embodiment; Figure 3 This is a flowchart illustrating a vehicle control method according to an exemplary embodiment; Figure 4 This is a flowchart illustrating a vehicle control method according to an exemplary embodiment; Figure 5 This is a flowchart illustrating a vehicle performing a welcoming operation according to an exemplary embodiment; Figure 6 This is a block diagram illustrating a vehicle control device according to an exemplary embodiment; Figure 7 This is a block diagram illustrating an electronic device according to an exemplary embodiment. Detailed Implementation

[0018] The specific embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit this disclosure.

[0019] Before detailing the specific implementation methods of this disclosure, the application scenarios of this disclosure are first explained below. This disclosure can be applied to keyless vehicle unlocking scenarios. In existing vehicle control technologies, when a user approaches a target vehicle with a mobile terminal, the system's judgment of the unlocking trigger condition is limited to instantaneous distance or identity snapshot data. As a result, the system cannot distinguish whether the user is actively approaching the vehicle to get in, or is just passing by or making a brief stop.

[0020] For example, in a parking lot scenario, a user carrying a mobile device walks around a target vehicle to check its condition. During this time, the distance between the mobile device and the vehicle briefly enters a preset threshold range. Based on current technology, the system only detects that the distance meets the condition and incorrectly interprets this behavior as an intention to get into the vehicle, thus triggering the welcome lights to illuminate and the door to unlock. The user's actual behavior is lateral movement without a direct trajectory towards the door, but the system, lacking continuous monitoring of the movement trend, cannot identify this behavior as unintentional entry. Therefore, in public areas with high traffic volume, such false triggers not only disrupt the user's normal operating procedures but may also lead to accidental opening of the door, posing a safety risk to nearby pedestrians and wasting vehicle energy.

[0021] To solve the above problems, Figure 1 This is a flowchart illustrating a vehicle control method according to an exemplary embodiment, such as... Figure 1 As shown, the method includes: Step 101: In response to the user's mobile terminal meeting the unlocking trigger condition of the target vehicle, the motion trajectory of the mobile terminal is obtained.

[0022] The mobile terminal can be used to unlock the target vehicle. The mobile terminal can be a portable electronic device carried by the user, such as a smartphone, smartwatch, or smart key. The mobile terminal has wireless communication capabilities and can exchange data with the target vehicle.

[0023] A motion trajectory refers to a continuously changing sequence of positions of a mobile terminal in space within a preset time period. By recording and analyzing motion trajectories, the movement trend of the mobile terminal and its user relative to a target vehicle can be characterized.

[0024] In one possible implementation, the unlocking trigger conditions include: the user passes identity authentication; and / or, the distance between the mobile terminal and the target vehicle is less than or equal to a first preset distance threshold.

[0025] Identity authentication refers to the process by which the system verifies the legitimacy of a user's identity. This ensures that only authorized users can trigger vehicle operations, effectively preventing unauthorized access and enhancing system security.

[0026] The distance between the mobile terminal and the target vehicle is less than or equal to a first preset distance threshold, which is used to initially screen whether the user is within the effective range where interaction with the vehicle is possible, thereby avoiding the accidental triggering of unnecessary operations when the user is far away from the vehicle.

[0027] This application's solution uses user authentication and / or the distance between the mobile terminal and the target vehicle being less than or equal to a first preset distance threshold as the unlocking trigger condition. This provides a more precise basis for subsequently acquiring the mobile terminal's movement trajectory and triggering the welcoming operation. When a user approaches the target vehicle with their mobile terminal, the system first attempts to authenticate their identity to confirm the user's legitimacy. Simultaneously, the system continuously monitors the distance between the mobile terminal and the target vehicle. Only when the user's identity is confirmed, or the distance between the mobile terminal and the target vehicle enters a preset effective range, or both conditions are met simultaneously, will the system determine that the unlocking trigger condition has been met. In this way, the system can effectively avoid false triggering due to a single distance judgment when the user unintentionally gets into the vehicle or only briefly passes by it.

[0028] Step 102: Trigger the target vehicle to perform a welcoming operation.

[0029] The triggering criteria for the welcoming operation include the movement trajectory.

[0030] A welcome sequence refers to a series of actions performed by a target vehicle to greet a user, indicating that the vehicle has recognized the user's arrival. Examples may include light shows, vehicle unlocking, etc.

[0031] The above solution combines the unlocking trigger conditions with the motion trajectory analysis of the mobile terminal, avoiding the situation where the welcome operation is accidentally triggered simply because the user is close to the vehicle, thereby improving the user experience and vehicle safety.

[0032] In one possible implementation, the authentication included in the unlocking trigger condition in step 101 above can be achieved in the following way: The vehicle's short-range wireless communication module (such as a BLE (Bluetooth Low Energy) module) broadcasts a handshake signal. When a mobile terminal moves within a preset range of the vehicle, it receives this handshake signal and initiates a handshake with the vehicle. After confirming a successful handshake, the vehicle wakes up the controller and the Ultra Wide Band (UWB) module based on the BLE module. Once the UWB module is activated, the controller verifies the identity based on the encrypted authentication information transmitted between the UWB module and the mobile terminal. This ensures that even if other Bluetooth devices approach, the system will not activate further if a secure handshake or encrypted authentication information cannot be completed, thus enhancing the security of identity authentication.

[0033] After successful identity authentication, the UWB module can obtain the distance between the mobile terminal and the target vehicle, and if the distance is less than or equal to a first preset distance threshold, it determines that the above-mentioned unlocking trigger condition is met.

[0034] For example, UWB signals are sent to the mobile terminal via multiple UWB receivers on the target vehicle, and the distance between the mobile terminal and the target vehicle is calculated by measuring the flight time of different UWB signals and the mobile terminal.

[0035] In some embodiments, such as Figure 2 As shown, obtaining the motion trajectory of the mobile terminal in step 101 above may include the following steps: Step 201: Obtain the location information of the mobile terminal through the ultra-wideband (UWB) communication module of the target vehicle.

[0036] Step 202: Obtain first point cloud data of multiple objects around the target vehicle using the LiDAR of the target vehicle.

[0037] LiDAR sensors emit laser beams and receive reflected light to generate three-dimensional point cloud data of the environment surrounding a target vehicle. This point cloud data can contain spatial location information of multiple objects, such as vehicles, pedestrians, and other objects.

[0038] In this embodiment of the disclosure, first point cloud data of multiple objects around the target vehicle can also be obtained by lidar.

[0039] Step 203: Based on the location information and the first point cloud data, determine the target point cloud data corresponding to the mobile terminal.

[0040] Step 204: Obtain the motion trajectory based on the target point cloud data.

[0041] By associating the high-precision location information provided by UWB with the point cloud data acquired by LiDAR, point cloud data belonging to mobile terminals can be accurately identified from complex environments.

[0042] After determining the target point cloud data corresponding to the mobile terminal, the movement path and trend of the mobile terminal can be inferred by continuously tracking the changes of these point cloud data over time.

[0043] The above solution integrates the location information provided by the ultra-wideband (UWB) communication module with the point cloud data acquired by radar, enabling precise positioning and identification of mobile terminals.

[0044] In some embodiments, such as Figure 3 As shown, step 203 above may include the following steps: Step 301: Cluster the first point cloud data of multiple objects to obtain multiple clusters.

[0045] In one possible implementation, a density-based clustering algorithm, such as DBSCAN, can be used. This algorithm can discover clusters of arbitrary shapes and effectively handle noisy points by setting a neighborhood radius and a minimum number of points to divide a set of points with sufficiently high density into clusters. In another possible implementation, a distance-based clustering algorithm, such as Euclidean clustering, can be used. This algorithm sets a distance threshold and considers points that are less than the threshold as part of the same cluster, thereby segmenting the point cloud into multiple independent objects.

[0046] Step 302: Based on location information, determine the target cluster corresponding to the mobile terminal from multiple clusters.

[0047] In one possible implementation, the centroid of each cluster can be calculated, and then the distance between the location information of the mobile terminal and the centroid of each cluster can be compared. The cluster with the closest distance can be selected as the target cluster corresponding to the mobile terminal.

[0048] Step 303: Use the point cloud data in the target cluster as the target point cloud data.

[0049] For example, when the LiDAR of a target vehicle scans the environment around the vehicle and generates the first point cloud data, this first point cloud data may contain multiple pedestrians, parked vehicles, and mobile devices carried by users. First, the DBSCAN clustering algorithm is performed on the first point cloud data. For example, a neighborhood radius (e.g., 0.3 meters) is set to group points that are less than this threshold into the same cluster, and a minimum number of points (e.g., 3) is set. If a point has at least 3 points within its 0.3-meter neighborhood, then this point is considered a core point. All core points form a cluster, thus dividing the point cloud data into multiple independent clusters, each representing an independent object.

[0050] Suppose the system identifies cluster A (possibly a street lamp), cluster B (possibly a pedestrian), cluster C (possibly a parked bicycle), and cluster D (possibly a user's mobile terminal). Simultaneously, the target vehicle's UWB module has acquired the mobile terminal's location information, such as coordinates (X1, Y1, Z1). Next, the system calculates the centroid coordinates of each cluster. For example, the centroids of clusters A, B, C, and D are calculated as (X_A, Y_A, Z_A), (X_B, Y_B, Z_B), (X_C, Y_C, Z_C), and (X_D, Y_D, Z_D), respectively. Then, the system calculates the Euclidean distance between the mobile terminal's UWB location and the centroid of each cluster. If the calculation shows that the distance between the mobile terminal's UWB location and the centroid of cluster D is the smallest and less than a preset matching threshold, then the system identifies cluster D as the target cluster corresponding to the mobile terminal. Finally, all point cloud data contained in cluster D, that is, all three-dimensional coordinate points constituting cluster D, are used as target point cloud data.

[0051] The above scheme, by introducing point cloud clustering and location-based cluster recognition, achieves accurate extraction of the point cloud data corresponding to the mobile terminal from multi-object point cloud data in complex environments. By clustering first and then matching, it accurately identifies discrete target clusters from complex radar point cloud data and effectively filters out environmental noise and isolated points. Combined with location information, it can accurately match the target cluster corresponding to the mobile terminal from numerous clusters, avoiding recognition errors caused by point cloud data confusion and ensuring the accuracy of motion trajectory acquisition.

[0052] In some embodiments, such as Figure 4 As shown, step 302 above may include the following steps: Step 401: Based on the location information, obtain the confidence level corresponding to each cluster.

[0053] The confidence level can characterize the degree to which the cluster is the target cluster.

[0054] Confidence score is an indicator used to quantify the degree of matching between each radar cluster and the location information of a mobile terminal. Its value reflects the likelihood that the cluster represents a mobile terminal. By introducing confidence score, the system can prioritize multiple potential targets.

[0055] Step 402: Select the cluster with the highest confidence level as the target cluster.

[0056] In this way, the vehicle directly compares the confidence scores of all clusters and selects the cluster with the highest confidence score as the target cluster.

[0057] In one possible implementation, after obtaining multiple clusters, feature information of each cluster is extracted. The feature information of the clusters includes at least the center position of the cluster, the average radial velocity, the number of point clouds, and the degree of dispersion of the point clouds.

[0058] By extracting features such as the center position of clusters, average radial velocity, number of points, and dispersion, the system can accurately describe the motion state of each cluster. These features are key inputs for associating UWB location information with clusters and calculating confidence levels. In particular, the number of points and dispersion help assess the credibility and size of targets, improving the accuracy of target association.

[0059] In one possible implementation, a first candidate target cluster is selected from multiple clusters based on location information and the center position of each cluster.

[0060] In this way, by utilizing the high-precision distance of UWB, the first candidate target cluster with the best location matching can be quickly screened out, thus achieving coarse correlation based on spatial distance.

[0061] Furthermore, step 401 above can be achieved through the following steps: S1. Calculate the absolute difference between the center distance and the UWB distance of each cluster.

[0062] S2. Compare the absolute difference with the preset distance threshold.

[0063] S3. Based on the comparison results, select the first candidate target cluster from multiple clusters.

[0064] Since the distance measurements of UWB and radar for the same physical target should be consistent within the error range, if the absolute difference is less than the preset distance threshold, the object corresponding to the cluster can be considered to be the mobile terminal, and thus the cluster can be regarded as the first candidate target cluster.

[0065] Among them, the sum of UWB ranging error, radar ranging error, and preset error compensation can be used as the preset distance threshold.

[0066] In this way, by setting a clear distance threshold, candidate targets that best match UWB identity information can be quickly and efficiently filtered from multiple clusters. This reduces computational load and improves the accuracy of coarse-grained target association in complex scenarios.

[0067] For example, a vehicle's radar detects pedestrian A and pedestrian B pushing a shopping cart, and the DBSCAN algorithm clusters them into two target clusters.

[0068] 1. The cluster features of pedestrian A are extracted as follows: Center location: Calculate the geometric center of the cluster corresponding to pedestrian A.

[0069] Average radial velocity: Calculate the average radial velocity of the point cloud data in the cluster corresponding to pedestrian A to reflect the overall motion trend.

[0070] Point cloud count: Count the number of point clouds in the cluster corresponding to pedestrian A.

[0071] Discreteness: Analyze the point cloud distribution range of the cluster corresponding to pedestrian A to reflect the size and shape of pedestrian A.

[0072] 2. Pedestrian shopping cart B-cluster feature extraction: Similarly, calculate the center position, average radial velocity, number of points, and dispersion of pedestrians and their shopping carts.

[0073] Pedestrian A and pedestrian B approach the vehicle simultaneously. The radar detects two target clusters: cluster A with its center at a distance of 2.6 meters and cluster B with its center at a distance of 4.1 meters.

[0074] The UWB module accurately measured the distance between pedestrian A and the vehicle as 2.5 meters.

[0075] Distance difference calculation: Ad_A = |2.5 - 2.6| = 0.1 meters Ad_B = |2.5 - 4.1| = 1.6 meters With a distance threshold set at 0.5 meters, cluster A is included in the first candidate target cluster because Ad_A (0.1 meters) is less than the distance threshold (0.5 meters). Cluster B is excluded because Ad_B (1.6 meters) is greater than the distance threshold.

[0076] It can be seen that by simply comparing distances, pedestrian A's UWB identity information can be quickly and accurately coarsely correlated with cluster A, while excluding cluster B, which has mismatched distances.

[0077] S4. Determine the estimated radial velocity of the mobile terminal using the UWB module; S5. Based on the radial velocity estimate of the mobile terminal and the average radial velocity of the first candidate target cluster, select the second candidate target cluster from the first candidate target cluster.

[0078] Based on coarse correlation, motion features are used for further confirmation to eliminate interference from static objects or objects whose motion patterns do not conform to the established rules. Differential or Kalman filtering is applied to UWB location information over multiple consecutive cycles to estimate the radial velocity of the mobile terminal (UWB-estimated radial velocity). For each candidate cluster in the first candidate target cluster, the difference between its average radial velocity and the user's radial velocity is calculated. A velocity threshold is set. If the velocity difference is less than the velocity threshold, the target passes the screening.

[0079] The above scheme, by introducing the estimation of UWB radial velocity and comparing it with the average radial velocity of the clusters, enables the system to further eliminate interfering targets that may be close in distance but have inconsistent motion patterns. This improves the accuracy of target association and its anti-interference capability.

[0080] S6. Based on the preset weights, perform weighted calculations on the center position, average radial velocity, and number of point clouds of each target cluster in the second candidate target cluster to determine the confidence level of each cluster in the second candidate target cluster.

[0081] For example, the confidence score Score_j can be calculated using the following formula: Score_j=w1 (1-Δd_j / Th_dist)+w2 (1-Δv_j / Th_vel)+w3 (size_j / MaxSize) Where w1, w2, and w3 are weighting coefficients, Th_dist and Th_vel are the set distance and velocity thresholds, Δd_j is the absolute difference between the center distance of each target cluster and the distance measured by UWB, Δv_j is the difference between the average radial velocity of each target cluster and the estimated radial velocity, size_j is the number of point clouds, and MaxSize is the expected maximum number of point clouds. A higher score indicates a greater likelihood that the cluster represents a mobile terminal. The expected maximum number of point clouds is the upper limit of the number of point clouds that a target (such as an adult) might generate in a specific scenario. For example, within a 10-meter radius around a vehicle, a normal-sized adult might generate a maximum of 100 point clouds.

[0082] In one possible implementation, a minimum confidence threshold is set; if the highest score is less than the confidence threshold, the association is considered to have failed.

[0083] By setting a minimum confidence score threshold, the system performs a secondary reliability check on the candidate cluster with the highest score. This ensures that only when the confidence level of the target association reaches a certain level will it be confirmed as the user's target cluster. This avoids erroneous associations in ambiguous scenarios, thereby improving the system's security.

[0084] After successful association, the system not only identifies the specific target in the radar point cloud but also binds the UWB identity tag to the radar target's ID and trajectory. All subsequent behavioral analysis will be based on this target identification. This multi-dimensional fusion scoring mechanism makes target association more comprehensive, avoids errors that may arise from single-dimensional judgment, and improves the success rate of accurately identifying user target clusters in complex scenarios.

[0085] This application's solution improves the reliability of accurately identifying the target cluster corresponding to the mobile terminal among multiple clusters by introducing confidence levels, thereby solving the problem of inaccurate target cluster identification. Then, the cluster with the highest confidence level is selected as the target cluster to ensure the accuracy of target cluster identification.

[0086] Once the target cluster is accurately identified, its point cloud data can be used as the corresponding target point cloud data for the mobile terminal, thereby obtaining a precise motion trajectory. Ultimately, the motion trajectory will serve as the basis for triggering the target vehicle to perform a welcoming operation, ensuring the accuracy of the welcoming operation. This avoids motion trajectory deviations and misinterpretations of user intent caused by inaccurate target cluster identification.

[0087] The following is a concrete example. Suppose that a LiDAR system detects multiple pedestrians around a vehicle and generates point cloud data containing these pedestrians. The system clusters this point cloud data, resulting in three clusters, labeled Cluster A, Cluster B, and Cluster C. Simultaneously, the vehicle's UWB module accurately measures the location information of the mobile terminal. To determine which cluster corresponds to the mobile terminal, the system calculates a confidence score for each cluster based on the mobile terminal's location information provided by UWB. Assume Cluster A has a confidence score of 0.9, Cluster B has a confidence score of 0.7, and Cluster C has a confidence score of 0.4. The system then compares these confidence score values ​​and finds that Cluster A has the highest confidence score. Therefore, the system identifies Cluster A as the target cluster corresponding to the mobile terminal. In this way, even in complex scenarios where multiple pedestrians are present simultaneously and close to the vehicle, the target cluster can be accurately identified.

[0088] The above-described solution, by introducing a confidence level mechanism, allows the system to quantitatively evaluate the credibility of each cluster as a target cluster. This enables the accurate selection of the cluster most likely representing the mobile terminal, even in the presence of location information errors or similar clusters. This improves the accuracy of target point cloud data determination, thereby ensuring the accuracy of mobile terminal motion trajectory acquisition. Ultimately, this allows motion trajectory-based greeting operations to more accurately determine user intent, avoiding false triggers caused by inaccurate target recognition in traditional solutions and enhancing the user experience.

[0089] After obtaining the motion trajectory through the above steps, in some embodiments, step 102 may include: triggering the target vehicle to perform a welcoming operation in response to the motion trajectory meeting preset welcoming conditions.

[0090] For example, the preset welcome conditions may include one or more of the following conditions: The motion trajectory indicates that the mobile terminal is in a preset recognition area, which is a pre-set area based on the position of the door handle of the target vehicle door; The motion trajectory indicates that the time the mobile terminal is in the preset recognition area is greater than or equal to a preset time threshold. The motion trajectory indicates that the user is approaching the target vehicle and is in a deceleration state; The motion trajectory indicates that the radial velocity of the mobile terminal is less than or equal to a preset speed threshold.

[0091] It should be noted that the location information, movement trend, and radial velocity of the mobile terminal can be determined based on the movement trajectory.

[0092] In this embodiment of the disclosure, to more accurately assess the user's behavior relative to key interaction points on the vehicle (such as the door handle), this solution converts the target position information, typically output by the radar sensor in polar coordinates, into Cartesian coordinates with the center of the door handle as the origin. Since the vehicle's millimeter-wave radar and UWB receiver are usually installed in different locations on the vehicle, their respective position information is in a coordinate system with their own location as the origin. Through coordinate transformation, all sensor data are unified into a common reference system.

[0093] In this embodiment of the disclosure, the preset identification area can be an area centered on the door handle, such as a fan-shaped area, a spherical area, or a cubic area. The system continuously monitors the location information of the mobile terminal to determine whether it is within the preset identification area.

[0094] In this embodiment, the motion trajectory represents the time the mobile terminal spends within a preset identification area that is greater than or equal to a preset time threshold. A time-based judgment is introduced to distinguish between a brief passage and an intended stay. When the mobile terminal enters the preset identification area, the system can start a timer to record the time the mobile terminal stays within that area. If the mobile terminal leaves the preset identification area, the timer is reset.

[0095] The motion trajectory represents a user approaching a target vehicle while decelerating, aiming to identify the user's active approach and preparation to stop behavior pattern. The system can continuously calculate the distance between the mobile terminal and the target vehicle and its rate of change to determine whether the user is approaching the vehicle. Simultaneously, by analyzing the mobile terminal's speed change trend, it determines whether it is decelerating, i.e., its instantaneous speed is continuously decreasing. This condition is met when the user approaches the vehicle and exhibits a deceleration trend.

[0096] The motion trajectory characterizes the radial velocity of the mobile terminal, indicating that it is less than or equal to a preset speed threshold. This quantifies the user's movement speed near the vehicle to confirm whether they have essentially stopped or are moving at a very slow speed. Radial velocity refers to the rate of change of distance between the mobile terminal and the target vehicle, i.e., the velocity component along the straight line connecting the mobile terminal and the target vehicle. The system can measure the radial velocity of the mobile terminal using methods such as ultra-wideband (UWB) ranging and compare it with the preset speed threshold. If the absolute value of the radial velocity is less than or equal to this threshold, it indicates that the mobile terminal is essentially stationary or moving at an extremely low speed, and this condition is met.

[0097] The system continuously calculates the distance between the user's current position and the door handle, comparing it to the distance from the previous moment to determine if the distance is continuously decreasing. Simultaneously, the system monitors whether the instantaneous speed shows a decreasing trend to confirm that the user is clearly and consistently moving towards the door and eventually stopping. It also monitors the user's instantaneous radial speed in real time; if the speed falls below a threshold, it is assumed that the user has stopped moving and is preparing to open the door, preventing accidental triggering while the user is still moving.

[0098] The above solution enables more accurate determination of whether a user truly intends to get in the car, avoids accidental vehicle unlocking, improves the accuracy of the welcome operation, and enhances the user experience.

[0099] After the above unlocking trigger conditions are met, the target vehicle can obtain the movement trajectory of the mobile terminal and trigger the target vehicle to perform a welcoming operation based on the movement trajectory.

[0100] This disclosure further proposes that triggering the target vehicle to perform a welcoming operation includes: triggering the target vehicle to perform a welcoming operation in response to the motion trajectory meeting preset welcoming conditions.

[0101] In this embodiment of the disclosure, the motion trajectory of the mobile terminal is received and analyzed in real time, and compared with preset welcoming conditions.

[0102] In this embodiment of the present disclosure, the vehicle controller can send control commands to relevant actuators such as door controllers and lighting controllers to achieve operations such as unlocking doors and turning on welcome lights; or, the welcome operation can be completed through the vehicle's internal communication bus system.

[0103] The above solution uses the motion trajectory as the trigger for the welcoming operation, compares it with the preset welcoming conditions of the motion trajectory, and combines it with the analysis of the user's dynamic behavior patterns. This allows the vehicle to understand the user's intentions more accurately, avoids unnecessary false triggers, and improves the user experience.

[0104] The welcoming process may only perform a single or fixed action, unable to dynamically adjust its content, resulting in a poor user experience. Therefore, this application further proposes... Figure 5 This is a flowchart illustrating a vehicle performing a welcoming operation according to an exemplary embodiment, such as... Figure 5 As shown, the method includes: Step 501: Control the welcome lights and / or ground projection lights to turn on.

[0105] Step 502: Unlock the vehicle.

[0106] Step 503: Open the door in the vehicle that is closest to the mobile terminal at a preset angle.

[0107] The system can be pre-configured with multiple welcome modes, each corresponding to different operation combinations. For example, the "light welcome" mode might only illuminate the lights, the "standard welcome" mode might illuminate the lights and unlock the vehicle, and the "advanced welcome" mode might illuminate the lights, unlock the vehicle, and automatically open the doors. Furthermore, the system can also set trigger priorities or conditions for different welcome actions based on the user's distance from the vehicle, speed, dwell time, and other movement trajectory characteristics, as well as the confidence level of the user's authentication. When specific conditions are met, the corresponding action is triggered, thus achieving the superposition or hierarchical execution of actions.

[0108] Upon receiving a welcome instruction, the vehicle's body controller can send control signals to the LED welcome lights or ground projection lights on the exterior of the vehicle. Welcome lights can be integrated, for example, below the rearview mirror, on the door handle, or on the side of the vehicle. Ground projection lights can be installed, for example, at the bottom of the door, and can project brand logos or welcome patterns onto the ground, illuminating them with a soft, gradual brightening or specific animation effects.

[0109] Upon receiving the unlock command, an unlock signal can be sent to the door controller via the vehicle network. The door controller then activates the door lock actuators to release the mechanical locks on all doors, possibly accompanied by audible and visual cues (such as flashing turn signals and an unlocking sound).

[0110] After the vehicle is unlocked, the system can use the mobile terminal's location information obtained from the UWB module or LiDAR to accurately determine which door the user is closest to. Then, the system sends a command to the electric door opening mechanism of that door via the door controller, driving the door to automatically open outwards at a preset opening angle (e.g., between 10 and 20 degrees), facilitating direct entry for the user. Alternatively, the vehicle is equipped with multiple door position sensors and electric door actuators. When the system recognizes a clear intention for the user to enter the vehicle and the vehicle is unlocked, it activates the electric opening function of the corresponding door based on the mobile terminal's real-time location data. During the door opening process, the angle sensor continuously monitors the opening angle; once the preset value is reached, the actuator stops operating, ensuring the door opens to a suitable and safe angle.

[0111] The above solution provides a variety of welcome operation options, enabling the vehicle to respond more precisely and intelligently based on the movement trajectory of the user's mobile terminal.

[0112] In one possible implementation, when the system determines that a user intends to board the vehicle using the aforementioned method, it can execute a welcoming operation according to a tiered strategy. For example, after confirming the intention to board, the controller can issue a sequence of instructions as follows: First, at time T, the vehicle's LED welcome lights illuminate, and simultaneously, the ground projection lights illuminate, projecting a welcome pattern onto the ground to create a welcoming atmosphere. Second, at time T+0.3, the system sends a command to the door lock actuator via the CAN / LIN bus, causing the door to emit a slight unlocking sound, completing the unlocking action and allowing the user to enter. Finally, at time T+0.5, if the vehicle is equipped with an electric door, the system will determine the door closest to the mobile terminal based on the mobile terminal's real-time location and send a command to that door actuator, causing it to automatically open outwards at a preset 15-degree angle, facilitating easy entry for the user. This step-by-step welcoming operation enhances the user experience and improves intelligence and convenience.

[0113] Figure 6 This is a block diagram illustrating a vehicle control device according to an exemplary embodiment, such as... Figure 6 As shown, the apparatus for business processing may include: The acquisition module 601 is used to acquire the movement trajectory of the mobile terminal in response to the user's mobile terminal meeting the unlocking trigger condition of the target vehicle; the mobile terminal is used to unlock the target vehicle. Trigger module 602 is used to trigger the target vehicle to perform a welcoming operation, wherein the triggering basis of the welcoming operation includes the motion trajectory.

[0114] Optionally, triggering the target vehicle to perform a welcoming operation includes: When the motion trajectory meets the preset welcoming conditions, the target vehicle is triggered to perform a welcoming operation.

[0115] Optionally, the preset welcoming conditions include one or more of the following conditions: The motion trajectory indicates that the mobile terminal is in a preset recognition area, which is a pre-set area based on the position of the door handle of the target vehicle door; The motion trajectory indicates that the time the mobile terminal is in the preset recognition area is greater than or equal to a preset time threshold. The motion trajectory indicates that the user is approaching the target vehicle and that the user is in a deceleration state; The motion trajectory indicates that the radial velocity of the mobile terminal is less than or equal to a preset speed threshold.

[0116] Optionally, the acquisition module 601 is configured to: The process of obtaining the motion trajectory of the mobile terminal includes: The location information of the mobile terminal is obtained through the ultra-wideband (UWB) communication module of the target vehicle; The first point cloud data of multiple objects around the target vehicle are obtained by the lidar of the target vehicle; Based on the location information and the first point cloud data, the target point cloud data corresponding to the mobile terminal is determined; The motion trajectory is obtained based on the target point cloud data.

[0117] Optionally, the acquisition module 601 is configured to: The step of determining the target point cloud data corresponding to the mobile terminal based on the location information and the first point cloud data includes: Cluster the first point cloud data of the multiple objects to obtain multiple clusters; Based on the location information, the target cluster corresponding to the mobile terminal is determined from the plurality of clusters; The point cloud data in the target cluster is used as the target point cloud data.

[0118] Optionally, the acquisition module 601 is configured to: Based on the location information, the confidence level corresponding to each cluster is obtained, and the confidence level represents the degree of confidence that the cluster is the target cluster; The cluster with the highest confidence level is selected as the target cluster.

[0119] Optionally, the unlocking trigger condition includes: The user is authenticated; and / or, The distance between the mobile terminal and the target vehicle is less than or equal to a first preset distance threshold.

[0120] Optionally, the welcoming operation includes one or more of the following: Control the illumination of welcome lights and / or floor projection lights; Unlock the vehicle; Unlock the vehicle and open the door in the vehicle that is closest to the mobile terminal at a preset angle.

[0121] Figure 7 This is a block diagram illustrating an electronic device 1000 according to an exemplary embodiment. For example... Figure 7As shown, the electronic device 1000 may include: a processor 1001 and a memory 1002. The electronic device 1000 may also include one or more of a multimedia component 1003, an input / output (I / O) interface 1004, and a communication component 1005.

[0122] The processor 1001 controls the overall operation of the electronic device 1000 to complete all or part of the steps in the vehicle control method described above. The memory 1002 stores various types of data to support the operation of the electronic device 1000. This data may include, for example, instructions for any application or method operating on the electronic device 1000, and application-related data such as contact data, sent and received messages, pictures, audio, video, etc. The memory 1002 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. Multimedia component 1003 may include a screen and an audio component. The screen may be, for example, a touchscreen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in memory 1002 or transmitted via communication component 1005. The audio component also includes at least one speaker for outputting audio signals. I / O interface 1004 provides an interface between processor 1001 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual or physical buttons. Communication component 1005 is used for wired or wireless communication between the electronic device 1000 and other devices. Wireless communication may include Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, or 4G, or a combination of these. Therefore, the corresponding communication component 1005 may include a Wi-Fi module, a Bluetooth module, or an NFC module.

[0123] In an exemplary embodiment, the electronic device 1000 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the vehicle control method described above.

[0124] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the vehicle control method described above. For example, the computer-readable storage medium may be the memory 1002 including program instructions, which may be executed by the processor 1001 of the electronic device 1000 to complete the vehicle control method described above.

[0125] In another exemplary embodiment, a computer program product is also provided, which includes a computer program executable by a processor, which, when executed by the processor, implements the steps of the vehicle control method described above.

[0126] The preferred embodiments of this disclosure have been described in detail above with reference to the accompanying drawings. However, this disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of this disclosure, various simple modifications can be made to the technical solutions of this disclosure, and these simple modifications all fall within the protection scope of this disclosure.

[0127] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.

[0128] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.

Claims

1. A method for vehicle control, characterized in that, The method includes: In response to the user's mobile terminal meeting the unlocking trigger condition of the target vehicle, the movement trajectory of the mobile terminal is acquired; the mobile terminal is used to unlock the target vehicle. The target vehicle is triggered to perform a welcoming operation, wherein the triggering basis for the welcoming operation includes the movement trajectory.

2. The method according to claim 1, characterized in that, The process of triggering the target vehicle to perform the welcoming operation includes: When the motion trajectory meets the preset welcoming conditions, the target vehicle is triggered to perform a welcoming operation.

3. The method according to claim 1, characterized in that, The preset welcoming conditions include one or more of the following conditions: The motion trajectory indicates that the mobile terminal is in a preset recognition area, which is a pre-set area based on the position of the door handle of the target vehicle door; The motion trajectory indicates that the time the mobile terminal is in the preset recognition area is greater than or equal to a preset time threshold. The motion trajectory indicates that the user is approaching the target vehicle and that the user is in a deceleration state; The motion trajectory indicates that the radial velocity of the mobile terminal is less than or equal to a preset speed threshold.

4. The method according to claim 1, characterized in that, The process of obtaining the motion trajectory of the mobile terminal includes: The location information of the mobile terminal is obtained through the ultra-wideband (UWB) communication module of the target vehicle; The first point cloud data of multiple objects around the target vehicle are obtained by the lidar of the target vehicle; Based on the location information and the first point cloud data, the target point cloud data corresponding to the mobile terminal is determined; The motion trajectory is obtained based on the target point cloud data.

5. The method according to claim 4, characterized in that, The step of determining the target point cloud data corresponding to the mobile terminal based on the location information and the first point cloud data includes: Cluster the first point cloud data of the multiple objects to obtain multiple clusters; Based on the location information, the target cluster corresponding to the mobile terminal is determined from the plurality of clusters; The point cloud data in the target cluster is used as the target point cloud data.

6. The method according to claim 5, characterized in that, The step of determining the target cluster corresponding to the mobile terminal from the plurality of clusters based on the location information includes: Based on the location information, the confidence level corresponding to each cluster is obtained, and the confidence level represents the degree of confidence that the cluster is the target cluster; The cluster with the highest confidence level is selected as the target cluster.

7. The method according to claim 1, characterized in that, The unlocking trigger conditions include: The user is authenticated; and / or, The distance between the mobile terminal and the target vehicle is less than or equal to a first preset distance threshold.

8. The method according to any one of claims 1 to 7, characterized in that, The welcoming operation includes one or more of the following: Control the illumination of welcome lights and / or floor projection lights; Unlock the vehicle; Unlock the vehicle and open the door in the vehicle that is closest to the mobile terminal at a preset angle.

9. An electronic device, characterized in that, include: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method according to any one of claims 1-8.

10. A vehicle, characterized in that, The vehicle includes the electronic equipment described in claim 9.

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