Method, device and equipment for preventing rear-end collision during vehicle lane changing process

Abstract

The application discloses a control method, device and equipment for preventing rear-end collision of a rear vehicle in a lane-changing process of a vehicle, and the method comprises the following steps: identifying a vehicle entering a pre-turning lane according to vehicle lane-changing detection; evaluating a collision risk between the vehicle and the rear vehicle according to a result of vehicle lane-changing identification; and performing a control operation of active avoidance of rear-end collision on the vehicle according to the collision risk of the vehicle. The application aims to solve the problems that the lane-changing of the vehicle is determined by a static mode, the vehicle parameter control is not accurate, and the vehicle avoidance strategy is simple in the lane-changing process. The collision risk of rear-end collision is comprehensively evaluated by acquiring different vehicle distance information, vehicle speed information and time information, so that the vehicle performs different control strategy operations, the driving safety is significantly improved, the rear-end collision accidents caused by improper lane-changing are reduced, the driving efficiency is improved, and a more comfortable and accurate driving experience is provided for the driver.

Description

Technical Field

[0001] This application relates to the field of vehicle control, and in particular to a control method, device, and equipment for preventing rear-end collisions during a vehicle lane change. Background Technology

[0002] With the rapid development of the automotive industry and increasingly busy road traffic, road safety, especially rear-end collisions during lane changes, has become a critical issue that urgently needs to be addressed. Traditional driver assistance systems, such as rearview mirrors and blind spot monitoring systems, can play a certain role in most situations, but their limitations are becoming increasingly apparent in complex and ever-changing traffic environments. To solve this problem, developing a more intelligent and real-time lane change assistance system is particularly important. Some existing systems use a static approach to determine lane change safety, relying solely on parameters such as current distance and speed, without considering the dynamic changes of following vehicles, such as acceleration and deceleration. This approach is prone to misjudgment in complex and ever-changing traffic environments. For example, if the system still judges lane change safety based on static parameters when a following vehicle is accelerating, a rear-end collision may occur. Static judgment methods typically cannot update the dynamic information of following vehicles in real time, thus failing to reflect changes in the traffic environment in a timely manner. This may cause the system to fail to make accurate judgments at critical moments, thereby increasing the risk of accidents.

[0003] While some existing systems consider vehicle parameters, they typically focus only on certain parameters, such as distance and speed, neglecting relative speed and other crucial information. This incomplete information acquisition can lead to inaccuracies in the system's avoidance strategy formulation. Existing systems often employ relatively simple algorithms, unable to provide optimal avoidance strategies based on comprehensive information. For example, when the system detects a vehicle accelerating towards it from behind, it might simply issue a warning or restrict lane changes, failing to develop more flexible avoidance strategies tailored to the specific situation. Furthermore, existing systems often employ fixed control strategies, unable to adapt to factors such as driver style and road conditions. This can result in the system failing to provide effective assistance to the driver in certain situations, and may even interfere with normal driving. Summary of the Invention

[0004] The primary objective of this application is to provide a control method for preventing rear-end collisions during lane changes. This method addresses issues such as relying on static lane change judgments, inaccurate vehicle parameter control, and simplistic avoidance strategies, which often lead to rear-end collisions. This technical method comprehensively assesses the collision risk by acquiring different distance, speed, and time information, thereby enabling the vehicle to execute different control strategies. This approach significantly improves driving safety, reduces rear-end collisions caused by improper lane changes, enhances driving efficiency, and provides drivers with a more comfortable and accurate driving experience.

[0005] To achieve the above objectives, this application provides a control method for preventing rear-end collisions during a vehicle lane change, the method comprising the following steps:

[0006] Based on vehicle lane change detection, the vehicle entering the pre-turn lane is identified;

[0007] Based on the results of the lane change recognition of the vehicle, assess the collision risk between the vehicle and the following vehicle;

[0008] Based on the collision risk between the vehicle and the following vehicle, the vehicle performs active rear-end collision avoidance control operations.

[0009] In one embodiment, the step of identifying the vehicle entering the pre-turn lane based on vehicle lane change detection further includes:

[0010] Detect whether the front of the vehicle is on the lane guide line, and calculate the angle between the vehicle and the lane guide line;

[0011] When the vehicle's vision module detects that the front of the vehicle is on the road guide line, the angle between the vehicle and the lane guide line reaches a preset angle value, and the lateral travel direction of the vehicle is consistent with the direction of the road guide line, the vehicle's lane change operation is recognized.

[0012] In one embodiment, the step of assessing the collision risk between the vehicle and the following vehicle based on the lane change recognition result further includes:

[0013] The relative speed between the vehicle and the vehicle behind it in the pre-turn lane is obtained based on the longitudinal speed of the vehicle and the speed of the vehicle behind it in the pre-turn lane.

[0014] Based on the relative speed and distance between the vehicle and the following vehicle in the pre-turn lane, calculate the time at which a collision risk occurs between the vehicle and the following vehicle in the pre-turn lane;

[0015] Based on the time of collision risk between the vehicle and the following vehicle in the pre-turning lane, calculate the derivative of the time of collision risk between the vehicle and the following vehicle in the pre-turning lane.

[0016] Based on the time of the collision risk between the vehicle and the following vehicle in the pre-turn lane and the derivative value, assess whether there is a collision risk between the vehicle and the following vehicle in the pre-turn lane.

[0017] In one embodiment, the step of assessing whether there is a collision risk between the vehicle and the following vehicle in the pre-turning lane based on the time and derivative of the collision risk between the vehicle and the following vehicle in the pre-turning lane further includes:

[0018] When the time of collision risk between the vehicle and the following vehicle and when the derivative value is within the first preset threshold range, it is determined that there is a first-level collision risk between the vehicle and the following vehicle in the pre-turning lane.

[0019] When the time of collision risk between the vehicle and the following vehicle and when the derivative value is within the second preset threshold range, it is determined that there is a second level of collision risk between the vehicle and the following vehicle in the pre-turning lane.

[0020] When the time of collision risk between the vehicle and the following vehicle and when the derivative value is within the third preset threshold range, it is determined that there is a level 3 collision risk between the vehicle and the following vehicle in the pre-turning lane.

[0021] When the time of collision risk between the vehicle and the following vehicle and the derivative value are within the fourth preset threshold range, it is determined that there is no collision risk between the vehicle and the following vehicle in the pre-steering lane.

[0022] In one embodiment, the step of performing active rear-end collision avoidance control operations on the vehicle based on the collision risk between the vehicle and the following vehicle further includes:

[0023] When it is determined that there is a Level 1 collision risk between the vehicle and a following vehicle in the pre-turning lane, a lane-changing control operation is performed on the vehicle.

[0024] When it is determined that there is a level 2 collision risk between the vehicle and a following vehicle in the pre-turning lane, a braking and lane-changing control operation is performed on the vehicle.

[0025] When it is determined that there is a level 3 collision risk between the vehicle and a following vehicle in the pre-turning lane, the vehicle is subjected to an acceleration lane change control operation.

[0026] When it is determined that there is no risk of collision between the vehicle and the following vehicle in the pre-turning lane, a normal lane change control operation is performed on the vehicle.

[0027] In one embodiment, prior to the step of identifying the vehicle entering the pre-turn lane based on vehicle lane change detection, the method further includes:

[0028] Detect the operating status of the vehicle;

[0029] When the vehicle is in a fault-free operating state, the step of identifying the vehicle that has entered the pre-turning lane based on the vehicle lane change detection is performed.

[0030] In one embodiment, the method further includes:

[0031] When the vehicle performs a lane-change stop control operation, the vehicle refuses the lane change and provides a voice reminder;

[0032] When the vehicle performs a braking and lane-changing control operation, the vehicle performs active braking and issues a voice warning.

[0033] When the vehicle performs an acceleration lane change control operation, the vehicle actively accelerates and provides a voice prompt.

[0034] When the vehicle performs a normal lane change control operation, the vehicle does not take any active action and provides a voice prompt.

[0035] In addition, to achieve the above objectives, this application also provides a control device for preventing rear-end collisions during a vehicle lane change, comprising: a lane change recognition module, a risk assessment module, and a vehicle control module;

[0036] The lane change recognition module identifies vehicles that have entered the pre-turn lane based on vehicle lane change detection.

[0037] The risk assessment module assesses the collision risk between the vehicle and the following vehicle based on the results of the vehicle's lane change recognition.

[0038] The vehicle control module performs active rear-end collision avoidance control operations on the vehicle based on the collision risk between the vehicle and the following vehicle.

[0039] Furthermore, to achieve the above objectives, this application also provides a control device for preventing rear-end collisions during a vehicle lane change. The control device for preventing rear-end collisions during a vehicle lane change includes: a memory, a processor, and a processing program for preventing rear-end collisions during a vehicle lane change, stored in the memory and executable on the processor. When the processing program for preventing rear-end collisions during a vehicle lane change is executed by the processor, it implements the steps of the control method for preventing rear-end collisions during a vehicle lane change.

[0040] In addition, to achieve the above objectives, this application also provides a readable storage medium storing a control program for preventing rear-end collisions during a vehicle lane change. When the control program for preventing rear-end collisions during a vehicle lane change is executed by a processor, it implements the steps of the above-described control method for preventing rear-end collisions during a vehicle lane change.

[0041] The above-mentioned one or more technical solutions provided in this application may have the following advantages or at least achieve the following technical effects:

[0042] This application discloses a control method, device, and equipment for preventing rear-end collisions during lane changes, relating to the field of vehicle control. The method includes the following steps: identifying vehicles entering a pre-turn lane based on lane change detection; assessing the collision risk of the vehicle based on the lane change identification result; and executing corresponding control strategies on the vehicle based on the collision risk. Advanced sensor technologies (such as ultrasonic radar, cameras, and lidar) are used to acquire real-time information about surrounding vehicles, including distance, speed, and position. Combined with the dynamic changes of following vehicles (such as acceleration and deceleration), the lane change risk is comprehensively assessed. This requires the system to have rapid response and accurate analysis capabilities. Based on the above information, the system can intelligently determine whether a lane change is safe, or, if necessary, remind the driver to stop the lane change to ensure driving safety. This application aims to solve the problem of rear-end collisions during lane changes due to insufficient observation or blurred vision in the rearview mirror. By comprehensively assessing the risk of rear-end collisions by acquiring different vehicle distance, speed, and location information, the vehicle can execute corresponding control strategies. This method will significantly improve driving safety, reduce rear-end collisions caused by improper lane changes, improve driving efficiency, and provide drivers with a more comfortable and convenient driving experience. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0044] Figure 1 This is a flowchart illustrating Embodiment 1 of the control method for preventing rear-end collisions during lane changing proposed in this application.

[0045] Figure 2 This is a flowchart illustrating Embodiment 2 of the control method for preventing rear-end collisions during lane changes proposed in this application.

[0046] Figure 3 This is a flowchart illustrating Embodiment 3 of the control method for preventing rear-end collisions during lane changes proposed in this application.

[0047] Figure 4 This is a flowchart illustrating Embodiment 4 of the control method for preventing rear-end collisions during lane changes proposed in this application.

[0048] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0049] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0050] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a specific posture. If the specific posture changes, the directional indicators will also change accordingly.

[0051] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the use of "and / or" or "and / or" throughout the text includes three parallel solutions. For example, "A and / or B" includes solution A, solution B, or a solution that simultaneously satisfies A and B. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0052] The intelligent lane change assist system combines advanced sensor technology, artificial intelligence algorithms, and vehicle dynamics models to achieve real-time, dynamic lane change risk assessment and decision support. It utilizes multiple sensors, including ultrasonic radar, cameras, and lidar, to acquire real-time information about the vehicle's surrounding environment, including the distance, speed, and direction of following vehicles. Ultrasonic radar detects the distance, speed, and relative position of following vehicles. Cameras capture images of the vehicle's surroundings, including lane lines, traffic signs, following vehicles, and other obstacles. LiDAR provides high-precision 3D environmental data, including the shape, position, and speed of objects. Preliminary processing, such as noise reduction, calibration, and synchronization, is performed on data from different sensors. The data is converted into a unified format for subsequent fusion and analysis. Fusion algorithms integrate data from different sensors, improving accuracy and reliability. Algorithms reduce false alarms and false negatives, providing more comprehensive environmental perception. A risk assessment model is established based on vehicle dynamic characteristics (such as acceleration, deceleration, and steering angle).

[0053] The risk assessment model is trained and optimized using machine learning algorithms. Historical and real-time data are used to continuously update the model, improving prediction accuracy and adaptability. Real-time assessment of lane change risks is performed based on fused sensor data. Potential collisions or hazardous situations during lane changes are predicted. The risk assessment model is continuously learned and optimized through machine learning algorithms to improve prediction accuracy. Cameras and sensors are used to identify driver behavior and intentions, such as steering wheel movements, braking, and acceleration. Based on driver behavior and style, the assistance system's prompts and decisions are intelligently adjusted to improve system adaptability and user experience. High-precision maps and positioning technology are used to obtain the vehicle's precise location on the road in real time. Combined with road information, such as lane lines and traffic signs, the accuracy of lane change decisions is improved. Vehicle-to-everything (V2X) technology enables real-time communication between vehicles, sharing driving information. Cooperative driving strategies are used to improve vehicle coordination and safety in complex traffic environments. High-precision map data, including detailed information such as lane lines, traffic signs, and road curvature, is used to obtain the vehicle's precise location on the road. GPS, inertial navigation systems, and map matching technology are combined to achieve real-time vehicle positioning. Improve the accuracy and reliability of vehicle positioning on the road. For example, when obstacles or traffic congestion are detected ahead, the system may suggest avoiding lane changes. Utilize road information from high-precision maps to improve the accuracy of lane-change decisions.

[0054] Changing lanes is a common maneuver while driving, but it is also a frequent source of accidents. Due to factors such as inattentive driver observation, blurred rearview mirror vision, and misjudgment, rear-end collisions during lane changes are common. To mitigate this risk, modern vehicles are equipped with advanced driver assistance systems, including methods for preventing rear-end collisions during lane changes. To address these issues, this application proposes a first embodiment of a control method for preventing rear-end collisions during lane changes; please refer to... Figure 1 The method includes steps S10 to S30:

[0055] Step S10: Identify the vehicle that has entered the pre-turn lane based on the vehicle lane change detection.

[0056] Step S20: Based on the result of the lane change recognition of the vehicle, assess the collision risk between the vehicle and the following vehicle;

[0057] Step S30: Based on the collision risk between the vehicle and the following vehicle, perform active rear-end collision avoidance control operations on the vehicle.

[0058] It should be noted that, in this embodiment, to reduce the risk of rear-end collisions, modern vehicles are beginning to be equipped with advanced driver assistance systems, including a rear-end collision prevention control method during lane changes. The following is a detailed description of the control method for preventing rear-end collisions during lane changes:

[0059] Step S10, the triggering of vehicle lane change detection is usually achieved in a variety of ways, including but not limited to:

[0060] The driver triggers lane change detection by steering the steering wheel or by activating the lane change indicator (turn signal).

[0061] The vehicle's sensors (such as cameras, lidar, ultrasonic radar, etc.) detect changes in lane markings or the dynamics of surrounding vehicles, automatically triggering lane change detection.

[0062] In autonomous driving mode, the system automatically detects lane changes based on road information and traffic rules. After triggering lane change detection, the system needs to identify vehicles entering the pre-turn lane.

[0063] By utilizing sensors such as cameras, LiDAR, and ultrasonic radar mounted on the vehicle, information about the vehicle's surrounding environment is acquired in real time. Images captured by the cameras are processed to identify lane lines, traffic signs, following vehicles, and other obstacles. Image processing algorithms are used to detect and track following vehicles, obtaining information such as distance, speed, and direction. Based on data from the cameras and LiDAR, the system identifies the current vehicle's lane and the pre-turn lane. Through image processing and machine learning algorithms, vehicles entering the pre-turn lane are identified and classified (e.g., cars, trucks, motorcycles). To improve the accuracy and reliability of identification, the system needs to fuse and verify data from different sensors.

[0064] Data from different sensors undergoes denoising, calibration, and synchronization to ensure accuracy and consistency. A fusion algorithm integrates data from various sensors, improving accuracy and reliability. By comparing data from different sensors, the accuracy and completeness of the data are verified, reducing false alarms and missed alarms.

[0065] In step S20, after identifying a vehicle entering the pre-turn lane, the system needs to assess the collision risk between the vehicle and the following vehicle. This step typically involves establishing a risk assessment model based on vehicle dynamic characteristics (such as acceleration, deceleration, and steering angle). The risk assessment model is usually related to the vehicle's motion state, including the speed, acceleration, deceleration, and steering angle of the current vehicle and the following vehicle.

[0066] Distance: The distance between the current vehicle and the vehicle behind, obtained in real time through sensor data. Relative Speed: The relative speed between the current vehicle and the vehicle behind, used to determine whether the vehicle behind is approaching or moving away.

[0067] Road conditions: These include lane width, road curvature, and road surface condition, which can affect vehicle handling and stability.

[0068] Traffic environment: This includes the dynamics of surrounding vehicles, traffic flow, traffic signals, etc., which may affect the vehicle's trajectory and speed.

[0069] To improve the accuracy of risk assessment, the system typically uses machine learning algorithms to train and optimize the risk assessment model. This step usually involves collecting historical and real-time data, including information such as vehicle motion status, distance between vehicles, relative speed, road conditions, and traffic environment. Machine learning algorithms (such as support vector machines, neural networks, and decision trees) are used to train the risk assessment model, enabling it to accurately predict collision risks. By continuously adjusting the model's parameters and structure, the predictive performance is optimized, improving accuracy and adaptability. Real-time data is used to continuously update the model, allowing it to adapt to different road and traffic environments. Based on the results of the risk assessment model, the system can classify collision risks into different levels, such as low risk, medium risk, and high risk. Different risk levels correspond to different control measures and warning methods. Furthermore, collision risk assessment needs to be performed in real time so that the system can take timely control measures. Therefore, the system needs to have efficient data processing capabilities and a rapid decision-making response speed.

[0070] Step S30: Based on the collision risk level, the system needs to formulate corresponding control strategies to actively avoid rear-end collision risks. Control strategies typically include the following:

[0071] Warning prompt: When the risk of collision is low, the system will issue a warning prompt to the driver through sound, light and other means to remind the driver to pay attention to the movement of vehicles behind.

[0072] Assisted braking: When the risk of collision is high, the system can automatically trigger the assisted braking function to slow down the vehicle and reduce the possibility of collision.

[0073] Lane keeping assist: When the risk of collision is extremely high, the system can force the vehicle to stay in the current lane and prohibit lane changing to avoid rear-end collisions.

[0074] Collaborative driving: In a vehicle-to-everything (V2X) environment, the system can communicate with surrounding vehicles in real time, share driving information, and use collaborative driving strategies to improve the coordination and safety of vehicles in complex traffic environments.

[0075] After formulating a control strategy, the system needs to execute corresponding control operations. Based on the control strategy, the system generates corresponding control commands, such as braking and steering commands. The system sends these commands to the vehicle's actuators (such as the braking and steering systems) to control the vehicle's motion. During the execution of control operations, the system needs to monitor the vehicle's motion and the dynamic changes of following vehicles in real time, and adjust the control strategy and commands according to the actual situation. In actively avoiding rear-end collisions, the system needs to fully consider driver intervention and feedback. When the system detects that the driver has taken countermeasures (such as braking or steering), the system can automatically exit control mode and hand over control to the driver. When the system executes control operations, it can provide prompts to the driver through sound, lights, etc., informing the driver of the control measures the system is taking. The system can receive driver feedback, such as satisfaction with the control effect and the clarity of system prompts, to optimize the system's control strategy and user experience. In a connected vehicle environment, the system can fully utilize cooperative driving technology to improve vehicle safety and coordination in complex traffic environments.

[0076] It is particularly important to note that vehicle-to-everything (V2X) technology enables real-time communication between vehicles, sharing driving information (such as location, speed, and direction), thereby improving vehicle coordination and safety. High-precision map data is used to obtain the precise location of vehicles on the road, combined with road information (such as lane markings and traffic signs) to improve the accuracy of lane-changing decisions. Based on vehicle-to-vehicle communication and road information, cooperative driving strategies, such as cooperative lane changing and cooperative braking, are formulated to improve vehicle safety and coordination in complex traffic environments. Real-time monitoring of the system's operational status and sensor data allows for timely detection and diagnosis of faults, preventing their impact on system performance. In a V2X environment, data security and privacy protection must be strengthened to prevent data leakage and misuse. Regular system upgrades and maintenance are essential to ensure that system performance and security meet the latest standards and requirements.

[0077] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in Embodiment 1 above can be referred to the above description, and will not be repeated hereafter. Please refer to Figure 2 In this embodiment, the step of identifying the vehicle entering the pre-turn lane based on vehicle lane change detection further includes:

[0078] Step S11: Detect whether the front of the vehicle is on the road guide line, and calculate the angle between the vehicle and the lane guide line.

[0079] Step S12: When the vehicle's vision module detects that the front of the vehicle is pressing on the road guide line, the angle between the vehicle and the lane guide line reaches a preset angle value, and the lateral travel direction of the vehicle is consistent with the direction of the road guide line, the vehicle's lane change operation is identified.

[0080] Specifically, in this embodiment, the detailed steps for vehicle lane change detection, particularly when identifying vehicles entering the pre-turn lane, include detecting the relationship between the vehicle's front and the road guide line, as well as calculating the angle between the vehicle and the lane guide line. The following is a detailed description of steps S11 and S12:

[0081] Step S11: Detect whether the front of the vehicle is on the road guide line and calculate the angle between the vehicle and the lane guide line. A camera (usually a front-view camera) mounted on the vehicle captures an image of the road ahead. The captured image should include a sufficient field of view to clearly show the lane lines and road guide lines (such as dashed lines, solid lines, arrows, etc.). The captured image is preprocessed, including noise reduction and contrast enhancement, to improve image quality. Image processing algorithms (such as edge detection, Hough transform, etc.) are used to identify the lane lines and road guide lines. In the processed image, the vehicle's own vision module (such as a camera and image processing algorithms) is used to identify the front of the vehicle. The precise position of the front of the vehicle is determined by its features (such as the front bumper, headlights, etc.). The position of the front of the vehicle is compared with the identified position of the road guide line to determine whether the front of the vehicle is on the road guide line. If the front of the vehicle coincides with or is very close to the road guide line (within a certain threshold), it is considered that the front of the vehicle is on the road guide line.

[0082] Based on the identified lane guide lines, their direction vectors are determined. This is typically achieved by calculating the slopes of multiple points on the lane guide lines. Using sensors installed on the vehicle (such as steering wheel angle sensors, vehicle speed sensors, etc.) and image processing algorithms, the vehicle's current direction of travel is determined. Alternatively, the direction vector of the vehicle's trajectory can be calculated using continuously captured image frames. The angle between the vehicle's direction of travel and the direction of the lane guide lines is calculated using the vector angle formula. The angle value represents the relative directional relationship between the vehicle and the lane guide lines.

[0083] Step S12: Confirm that the vehicle's front end, detected by the vehicle's vision module, is indeed aligned with the road guide line. Check if the calculated angle between the vehicle and the lane guide line reaches a preset angle value. This preset value is usually determined based on factors such as road design, traffic rules, and vehicle handling performance. Determine if the vehicle's lateral travel direction is consistent with the direction of the road guide line. This can be achieved by comparing the directions of the vehicle's travel direction vector and the lane guide line direction vector.

[0084] If the two directions are the same or very close (within a certain threshold), the vehicle's lateral travel direction is considered to be consistent with the direction of the road guide line. When all three conditions are met simultaneously—that is, the front of the vehicle is on the road guide line, the included angle reaches a preset value, and the lateral travel direction is consistent with the direction of the road guide line—the system can determine that the vehicle is performing a lane change operation. The system sends a confirmation signal to the driver or the autonomous driving system, indicating that a lane change operation has been detected. Simultaneously, the system can prepare to execute subsequent collision risk assessment and control operations. The system should be able to adapt to different road conditions and traffic environments, such as lanes of different widths and different road guide line styles. The system should ensure the accuracy and reliability of detection, avoiding false positives and false negatives. The system should be able to detect and process image data in real time to promptly identify lane change operations and take appropriate control measures. When identifying lane change operations, the system should fully consider safety factors to avoid unnecessary interference or danger to the driver or surrounding vehicles.

[0085] Based on the first and / or second embodiments of this application, in the third embodiment of this application, the content that is the same as or similar to that in embodiments one and two above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 3 In this embodiment, step S20, the step of assessing the collision risk between the vehicle and the following vehicle based on the lane change recognition result, further includes:

[0086] Step S21: Based on the longitudinal speed of the vehicle and the speed of the following vehicle in the pre-turn lane, obtain the relative speed between the vehicle and the following vehicle in the pre-turn lane.

[0087] Step S22: Calculate the time when a collision risk occurs between the vehicle and the following vehicle in the pre-turn lane based on the relative speed and distance between the vehicle and the following vehicle in the pre-turn lane.

[0088] Step S23: Calculate the derivative of the time of collision risk between the vehicle and the following vehicle in the pre-turn lane based on the time of collision risk between the vehicle and the following vehicle in the pre-turn lane.

[0089] Step S24: Based on the time of the collision risk between the vehicle and the following vehicle in the pre-turning lane and the derivative value, assess whether there is a collision risk between the vehicle and the following vehicle in the pre-turning lane.

[0090] It should be noted that in this embodiment, the assessment of the collision risk between the vehicle and the following vehicle is involved based on the lane change recognition result. Assessing the collision risk with the following vehicle is crucial during lane changes. This requires the system to acquire and process the relative speed and distance data between the vehicle and the following vehicle in real time, and then calculate the Time to Collision (TTC) and its derivative to accurately assess the collision risk. The following is a detailed description of the above steps:

[0091] Step S21: Obtain the relative speed between the current vehicle and the following vehicle. The longitudinal speed of the current vehicle is obtained through the vehicle's own sensors (such as speed sensors, radar, lidar, etc.). Using onboard radar, lidar, or cameras, combined with image processing and object tracking algorithms, the speed of the following vehicle in the pre-turn lane is identified and obtained. In some advanced autonomous driving systems, the speed information of the following vehicle can also be obtained through vehicle-to-everything (V2X) communication. Relative speed refers to the speed difference between the current vehicle and the following vehicle; the sign of the relative speed indicates the relative motion trend between the two vehicles.

[0092] Step S22: Calculate the time to collision risk by using onboard sensors (such as radar, lidar, or cameras) to measure the actual distance between the current vehicle and the vehicle behind. This typically involves processing images or radar signals to identify and track the position of the following vehicle. TTC refers to the time required for a collision to occur between the two vehicles while maintaining their current and relative speeds. A smaller TTC value indicates a higher risk of collision between the two vehicles; conversely, a larger TTC value indicates a lower risk of collision between the two vehicles.

[0093] Step S23: Calculate the derivative of TTC (i.e., the rate of change of TTC). Continuously acquire the speed data of the current vehicle and the following vehicle to calculate their respective rates of change. This can be achieved by differentiating the speed data. Differentiate the speed data of the current vehicle and the following vehicle to obtain their respective rates of change. This represents the instantaneous change in vehicle speed, i.e., acceleration. The rate of change of TTC represents the trend of TTC over time. The rate of change of TTC reflects the dynamic change of collision risk. If the rate of change of TTC is negative, it indicates that TTC is decreasing, i.e., the collision risk is increasing; if the rate of change of TTC is positive, it indicates that TTC is increasing, i.e., the collision risk is decreasing.

[0094] Step S24: Assess the risk of collision between the vehicle and the following vehicle. Based on safety standards and road conditions, set thresholds for TTC and TTC change rate. These thresholds are used to determine whether the collision risk between the current vehicle and the following vehicle is acceptable. Compare the calculated TTC and TTC change rate with the set thresholds. If the TTC is less than a certain threshold (indicating a collision is likely within a short time), or the TTC change rate is less than a negative threshold (indicating a rapidly decreasing TTC, i.e., a rapidly increasing collision risk), a collision risk is identified. If the assessment indicates a collision risk, the vehicle can issue a warning signal, adjust its speed, change lanes, or take other measures to avoid a collision. These measures should be determined based on the actual situation and the system's capabilities.

[0095] It is particularly important to ensure that the speed and distance data acquired from the sensors are accurate and reliable. This requires sensors with good accuracy and stability, and data processing algorithms capable of accurately identifying and tracking the position and speed of following vehicles. Calculation of TTC and TTC change rate needs to be performed in real time to enable timely collision avoidance measures. This requires the system to have high-speed data processing capabilities and a fast response speed. The evaluation algorithm should be adaptable to different road conditions, traffic environments, and weather conditions. For example, in low visibility conditions such as rain or fog, sensors may not accurately acquire speed and distance information of following vehicles; in such cases, the algorithm should be able to take appropriate measures to reduce the false alarm rate. When assessing collision risk, the safety and reliability of the algorithm must be ensured to avoid unnecessary dangers caused by false alarms or missed alarms. Simultaneously, the algorithm should be able to handle abnormal situations, such as sensor malfunctions or data loss.

[0096] Further, in this embodiment, step 24, the step of assessing whether there is a collision risk between the vehicle and the following vehicle in the pre-turning lane based on the time and derivative value of the collision risk between the vehicle and the following vehicle in the pre-turning lane, further includes:

[0097] When the time of collision risk between the vehicle and the following vehicle and when the derivative value is within the first preset threshold range, it is determined that there is a first-level collision risk between the vehicle and the following vehicle in the pre-turning lane.

[0098] When the time of collision risk between the vehicle and the following vehicle and when the derivative value is within the second preset threshold range, it is determined that there is a second level of collision risk between the vehicle and the following vehicle in the pre-turning lane.

[0099] When the time of collision risk between the vehicle and the following vehicle and when the derivative value is within the third preset threshold range, it is determined that there is a level 3 collision risk between the vehicle and the following vehicle in the pre-turning lane.

[0100] When the time of collision risk between the vehicle and the following vehicle and the derivative value are within the fourth preset threshold range, it is determined that there is no collision risk between the vehicle and the following vehicle in the pre-steering lane.

[0101] It should be noted that, in this embodiment, accurately assessing the collision risk with following vehicles in the pre-turn lane is crucial during lane changing. This helps the system issue timely warnings and avoid potential collisions. By comprehensively considering the time frame and derivative of the collision risk, we can gain a more comprehensive understanding of the dynamic changes in collision risk, thereby making more accurate decisions.

[0102] The system determines a Level 1 collision risk by defining the Time to Collision (TTC) and its derivative as falling within a first preset threshold range. This first preset threshold range is typically set to represent a high-risk zone. A Level 1 collision risk exists between the vehicle and the following vehicle in the pre-steering lane when the TTC is short (i.e., a collision is imminent) and the derivative of the TTC is also large (i.e., the collision risk is rapidly increasing). This means the system needs to take immediate action, such as issuing emergency braking or obstacle avoidance commands, to prevent a collision. The system first calculates the TTC and its derivative between the vehicle and the following vehicle.

[0103] Then, these two values ​​are compared with a first preset threshold range. If both values ​​fall within this range, the system determines that there is a level 1 collision risk.

[0104] The setting of the first preset threshold range needs to take into account various factors, such as vehicle speed, road conditions, and traffic flow. When issuing emergency commands, the system should ensure that it does not pose additional risks to other road users.

[0105] A Level 2 collision risk is determined when both the Time to Collision Risk (TTC) and its derivative fall within a second preset threshold range. This second preset threshold range is typically set to represent a moderate risk level. A Level 2 collision risk exists between the vehicle and the following vehicle in the pre-steering lane when the TTC is relatively long but still within an acceptable range, and the derivative of the TTC is moderate (i.e., the collision risk is slowly increasing or remaining stable). This means the system needs to issue a warning to alert the driver and prompt appropriate evasive action. The system first calculates the TTC and its derivative between the vehicle and the following vehicle. These two values ​​are then compared to the second preset threshold range. If both values ​​fall within this range, the system determines that a Level 2 collision risk exists. The setting of the second preset threshold range should ensure the timeliness and accuracy of the warning. The system should consider the driver's reaction time and the vehicle's performance limitations when issuing a warning.

[0106] A Level 3 collision risk is determined when both the Time to Collision Risk (TTC) and its derivative fall within a third preset threshold range. This third preset threshold range is typically set to represent a low-risk zone. A Level 3 collision risk exists between the vehicle and the following vehicle in the pre-steering lane when the TTC is long and its derivative is small (i.e., the collision risk is slowly decreasing or remaining stable). This means the system can issue a mild warning or choose not to issue one, allowing the driver to decide based on the situation. The system calculates the TTC and its derivative between the vehicle and the following vehicle. These two values ​​are compared to the third preset threshold range. If both values ​​fall within this range, the system determines a Level 3 collision risk and issues a warning as needed. The setting of the third preset threshold range should ensure that it does not cause excessive interference to the driver. The system should consider the driver's driving habits and preferences when issuing warnings.

[0107] If no collision risk is determined, the Time to Collision Risk (TTC) and its derivative are both within the fourth preset threshold range. This fourth preset threshold range is typically set to represent a risk-free zone. When the TTC is very long and its derivative is close to zero (i.e., the collision risk is almost nonexistent or rapidly decreasing), there is no collision risk between the vehicle and the following vehicle in the pre-steering lane. This means the system can remain silent and not issue any warnings or instructions. The system calculates the TTC and its derivative between the vehicle and the following vehicle. These two values ​​are compared to the fourth preset threshold range.

[0108] If both values ​​fall within this range, the system determines there is no risk of collision. The setting of the fourth preset threshold range should ensure the stability and reliability of the system. When the system is in silent mode, it should continuously monitor road conditions to issue timely alerts or instructions when necessary.

[0109] Based on the first and / or second and / or third embodiments of this application, in the fourth embodiment of this application, the content that is the same as or similar to the above-described embodiments one, two, and three can be referred to the above description and will not be repeated hereafter. Based on this, please refer to... Figure 4 In this embodiment, step S30, the step of performing active rear-end collision avoidance control operations on the vehicle based on the collision risk between the vehicle and the following vehicle, further includes:

[0110] Step S31: When it is determined that there is a first-level collision risk between the vehicle and the following vehicle in the pre-turning lane, a lane-changing control operation is performed on the vehicle.

[0111] Step S32: When it is determined that there is a second-level collision risk between the vehicle and the following vehicle in the pre-turning lane, a braking and lane-changing control operation is performed on the vehicle.

[0112] Step S33: When it is determined that there is a third-level collision risk between the vehicle and the following vehicle in the pre-turning lane, the vehicle is given an acceleration lane change control operation.

[0113] Step S34: When it is determined that there is no risk of collision between the vehicle and the following vehicle in the pre-turning lane, a normal lane change control operation is performed on the vehicle.

[0114] Specifically, in this embodiment, step S30 is a crucial step. Based on the collision risk level between the vehicle and the following vehicle in the pre-turn lane, corresponding control operations are performed on the vehicle to ensure driving safety. The core task is to assess the collision risk between the vehicle and the following vehicle in the pre-turn lane and perform corresponding control operations according to the risk level. This includes operations such as stopping lane changes, braking lane changes, accelerating lane changes, and normal lane changes. These operations aim to avoid potential rear-end collisions and improve road safety and driving comfort. The following is a detailed description of step S30 and its sub-steps S31, S32, S33, and S34:

[0115] Step S31, Stop Lane Change. When there is a Level 1 collision risk (extremely high risk) between the vehicle and a following vehicle in the pre-turn lane, immediate measures are required to avoid an accident. The system immediately sends a stop lane change command to the vehicle. Upon receiving the command, the vehicle immediately stops the lane change and remains in its current lane. Simultaneously, the system may also need to issue an emergency warning to the driver, reminding them to pay attention to driving safety. When performing the stop lane change operation, the system should ensure that the vehicle can smoothly stop in its current lane, avoiding sudden changes in direction or abrupt braking. The system also needs to continuously monitor road conditions to take further evasive action if necessary.

[0116] Step S32, Braking and Lane Change. When there is a Level 2 collision risk between the vehicle and the following vehicle in the pre-turn lane—meaning the risk is high but there is still sufficient time and space to take measures to avoid an accident—the system sends a braking and lane change command to the vehicle. Upon receiving the command, the vehicle first decelerates and brakes to reduce the relative speed with the following vehicle. Simultaneously with braking, the vehicle gradually turns into the pre-turn lane, ensuring a smooth lane change during deceleration. After completing the lane change, the vehicle continues to travel at a low speed for a distance to maintain a safe distance from the following vehicle. When performing the braking and lane change operation, the system should ensure that the vehicle's braking and steering performance are in good condition. Simultaneously, the system also needs to consider the driver's reaction time and the vehicle's performance limitations to ensure the feasibility and safety of the operation.

[0117] Step S33, Accelerated Lane Change. When there is a Level 3 collision risk between the vehicle and the following vehicle in the pre-turn lane (i.e., the collision risk is low, but certain measures are still required to ensure safety), the system sends an accelerated lane change instruction to the vehicle. Upon receiving the instruction, the vehicle first accelerates slightly to increase the relative distance to the following vehicle. While accelerating, the vehicle gradually turns into the pre-turn lane, ensuring a smooth lane change during acceleration. After completing the lane change, the vehicle continues to travel at an appropriate speed. When performing the accelerated lane change operation, the system should ensure that the vehicle's acceleration and steering performance are in good condition. Simultaneously, the system also needs to consider factors such as road conditions and traffic flow to ensure that the accelerated lane change operation does not pose additional risks to other road users.

[0118] Step S34, Normal Lane Change. When there is no risk of collision between the vehicle and the vehicle behind it in the pre-turning lane (i.e., road conditions are good, traffic flow is moderate, and a sufficient safe distance is maintained between the vehicle and the vehicle behind), the system sends a normal lane change instruction to the vehicle. Upon receiving the instruction, the vehicle performs a smooth lane change operation according to the preset lane change trajectory and speed. During the lane change, the system continuously monitors road conditions and vehicle status to ensure the safety and stability of the lane change operation. When performing a normal lane change operation, the system should ensure that the vehicle's steering performance and stability are in good condition. Simultaneously, the system also needs to consider the driver's driving habits and preferences, as well as changes in road and traffic conditions, to provide a personalized lane change experience.

[0119] It is particularly important to note that the system should be able to quickly and accurately assess collision risks and immediately execute corresponding control operations when necessary. This requires the system to have efficient data processing capabilities and rapid decision-making abilities. The vehicle's braking performance, acceleration performance, and steering performance are all key factors affecting the effectiveness of step S30. Therefore, the system needs to regularly monitor and maintain vehicle performance to ensure it is in good condition. Although the system can automatically assess collision risks and execute corresponding control operations, driver involvement remains essential. The system should provide a clear and intuitive interface and prompts so that the driver can promptly understand road conditions and system status and react accordingly. Road conditions, traffic flow, weather, and other factors all affect the effectiveness of step S30. Therefore, the system needs to comprehensively consider these factors and dynamically adjust and optimize according to actual conditions.

[0120] Furthermore, in this embodiment, the method further includes: when the vehicle performs a lane-changing stop control operation, the vehicle processes the lane-changing refusal and provides a voice reminder;

[0121] When the vehicle performs a braking and lane-changing control operation, the vehicle performs active braking and issues a voice warning.

[0122] When the vehicle performs an acceleration lane change control operation, the vehicle actively accelerates and provides a voice prompt.

[0123] When the vehicle performs a normal lane change control operation, the vehicle does not take any active action and provides a voice prompt.

[0124] Specifically, in this embodiment, in addition to basic collision risk assessment and corresponding control operations, the vehicle lane change assist system or autonomous driving system can further refine the specific processing methods and voice prompt mechanisms under each control operation. The following is a detailed description of these steps:

[0125] When the system determines that there is a Level 1 collision risk between the vehicle and a following vehicle in the pre-turn lane, it will execute a lane-change stop control operation. The vehicle immediately stops the current lane-change maneuver and remains in the current lane. At this time, the vehicle's steering system is locked to prevent the vehicle from continuing to veer into the pre-turn lane. The system issues a voice alert to the driver via the vehicle's audio system, clearly stating, "High risk of collision ahead, lane change stopped, please stay in your current lane." This alert helps enhance the driver's safety awareness and makes them aware of the current system status.

[0126] When the system determines that there is a Level 2 collision risk between the vehicle and a following vehicle in the pre-turn lane, it will execute a braking lane change control operation. The vehicle will first decelerate and brake to reduce the relative speed with the following vehicle. This action is achieved through the vehicle's braking system, designed to reduce the likelihood of a collision. Simultaneously with braking, the system will issue a voice warning to the driver via the audio system, stating, "Collision risk ahead, braking lane change in progress, please remain vigilant." This warning helps remind the driver to pay attention to road conditions and prepare accordingly.

[0127] When the system determines that there is a Level 3 collision risk between the vehicle and a following vehicle in the pre-turn lane, it will execute an acceleration lane change control operation. The vehicle will accelerate slightly to increase the relative distance between itself and the following vehicle. This action is achieved through the vehicle's acceleration system, designed to create more space and time for the lane change operation. Simultaneously with acceleration, the system will issue a voice alert to the driver via the audio system, stating, "Collision risk ahead, accelerating lane change, please maintain directional stability." This alert helps the driver understand the system's intentions and guides them to cooperate with the system's actions.

[0128] When the system determines that there is no collision risk between the vehicle and the following vehicle in the pre-turn lane, it will execute a normal lane change control operation without actively taking evasive action. In a normal lane change, the vehicle will smoothly change lanes according to the preset lane change trajectory and speed. At this time, the system does not require any additional active intervention from the vehicle. Although the system does not actively intervene, it will still issue a voice reminder to the driver via the audio system, stating, "Current road conditions are good, normal lane change is in progress." This reminder helps enhance the driver's confidence and makes them aware of the system's operational status. When executing the above steps, the system needs to comprehensively consider multiple factors, including the collision risk level, vehicle performance, driver participation, and road and traffic conditions. Simultaneously, the system must ensure the accuracy and timeliness of the voice reminders and warnings so that the driver can promptly understand the road conditions and system status and react accordingly.

[0129] Furthermore, the system needs to possess high reliability and stability to ensure accurate assessment of collision risks and execution of corresponding control actions under various complex road and traffic conditions. This requires the system to have efficient data processing capabilities, rapid decision-making abilities, and robust fault detection and recovery mechanisms.

[0130] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent scope of this application.

Claims

1. A control method for preventing a rear vehicle from colliding with a preceding vehicle during a lane change of the preceding vehicle, characterized by, The method comprises the following steps: According to the vehicle lane change detection, the vehicle entering the pre-turning lane is identified; According to the result of the vehicle lane change identification, the collision risk between the vehicle and the rear vehicle is evaluated; According to the collision risk between the vehicle and the rear vehicle, the control operation of active avoidance of rear-end collision is performed on the vehicle; The step of evaluating the collision risk between the vehicle and the rear vehicle according to the result of the vehicle lane change identification further comprises: According to the longitudinal speed of the vehicle and the speed of the rear vehicle on the pre-turning lane, the relative speed between the vehicle and the rear vehicle on the pre-turning lane is obtained; According to the relative speed and the distance between the vehicle and the rear vehicle on the pre-turning lane, the time of collision risk between the vehicle and the rear vehicle on the pre-turning lane is calculated; According to the time of collision risk between the vehicle and the rear vehicle on the pre-turning lane, the derivative value of the time of collision risk between the vehicle and the rear vehicle on the pre-turning lane is calculated; According to the time of collision risk between the vehicle and the rear vehicle on the pre-turning lane and the derivative value, it is evaluated whether there is a collision risk between the vehicle and the rear vehicle on the pre-turning lane.

2. The method of claim 1, wherein, The step of identifying the vehicle entering the pre-turning lane according to the vehicle lane change detection further comprises: Detecting whether the vehicle head is pressed on the road guide line and calculating the included angle between the vehicle and the lane guide line; When the vehicle head is detected by the visual module of the vehicle to be pressed on the road guide line, the included angle between the vehicle and the lane guide line reaches the preset angle value, and the lateral driving direction of the vehicle is consistent with the direction of the road guide line, the lane change operation of the vehicle is identified.

3. The method of claim 2, wherein, The step of evaluating whether there is a collision risk between the vehicle and the rear vehicle on the pre-turning lane according to the time of collision risk between the vehicle and the rear vehicle on the pre-turning lane and the derivative value further comprises: When the time of collision risk between the vehicle and the rear vehicle and the derivative value are in the first preset threshold interval, it is determined that there is a first level collision risk between the vehicle and the rear vehicle on the pre-turning lane; When the time of collision risk between the vehicle and the rear vehicle and the derivative value are in the second preset threshold interval, it is determined that there is a second level collision risk between the vehicle and the rear vehicle on the pre-turning lane; When the time of collision risk between the vehicle and the rear vehicle and the derivative value are in the third preset threshold interval, it is determined that there is a third level collision risk between the vehicle and the rear vehicle on the pre-turning lane; When the time of collision risk between the vehicle and the rear vehicle and the derivative value are in the fourth preset threshold interval, it is determined that there is no collision risk between the vehicle and the rear vehicle on the pre-turning lane.

4. The method of claim 3, wherein, The step of performing the control operation of active avoidance of rear-end collision on the vehicle according to the collision risk between the vehicle and the rear vehicle further comprises: When it is determined that there is a first level collision risk between the vehicle and the rear vehicle on the pre-turning lane, the control operation of stopping lane change is performed on the vehicle; performing a stop lane-changing control operation on the vehicle; performing an acceleration lane-changing control operation on the vehicle; performing a normal lane-changing control operation on the vehicle.

5. The method of claim 1, wherein, The method further comprises: detecting the working state of the vehicle; when the working state of the vehicle is in a working state indicated by no fault, performing the step of identifying the vehicle entering the pre-turning lane according to vehicle lane-changing detection.

6. The method of claim 4, wherein, The method further comprises: when the vehicle performs a stop lane-changing control operation, the vehicle performs a lane-changing refusal process and voice prompting; when the vehicle performs a brake lane-changing control operation, the vehicle performs an active braking process and voice warning; when the vehicle performs an acceleration lane-changing control operation, the vehicle performs an active acceleration process and voice prompting; when the vehicle performs a normal lane-changing control operation, the vehicle does not perform an active process and voice prompting.

7. A control device for preventing rear-end collisions during a vehicle lane change, characterized in that, The device comprises a lane-changing identification module, a risk assessment module and a vehicle control module. The lane-changing identification module identifies the vehicle entering the pre-turning lane according to vehicle lane-changing detection. The risk assessment module assesses the collision risk between the vehicle and the rear vehicle according to the result of the lane-changing identification of the vehicle. The vehicle control module performs a control operation of actively avoiding rear-end collision on the vehicle according to the collision risk between the vehicle and the rear vehicle. The risk assessment module obtains the relative speed between the vehicle and the rear vehicle on the pre-turning lane according to the longitudinal speed of the vehicle and the speed of the rear vehicle on the pre-turning lane; calculates the time of collision risk between the vehicle and the rear vehicle on the pre-turning lane according to the relative speed and the distance between the vehicle and the rear vehicle on the pre-turning lane; calculates the derivative value of the time of collision risk between the vehicle and the rear vehicle on the pre-turning lane according to the time of collision risk between the vehicle and the rear vehicle on the pre-turning lane; and assesses whether there is a collision risk between the vehicle and the rear vehicle on the pre-turning lane according to the time of collision risk between the vehicle and the rear vehicle on the pre-turning lane and the derivative value.

8. A control device for preventing rear-end collisions during a vehicle lane change, characterized in that, The control device for preventing rear-end collision of a vehicle during lane-changing process comprises a memory, a processor, and a vehicle lane-changing process control program for preventing rear-end collision stored on the memory and executable on the processor, and when the vehicle lane-changing process control program for preventing rear-end collision is executed by the processor, the steps of the vehicle lane-changing process control method for preventing rear-end collision according to any one of claims 1 to 6 are implemented.

9. A readable storage medium, characterized by, The readable storage medium stores a control program for preventing rear-end collision of a following vehicle during a vehicle lane-changing process, and the control program for preventing rear-end collision of a following vehicle during a vehicle lane-changing process, when executed by a processor, implements the steps of the control method for preventing rear-end collision of a following vehicle during a vehicle lane-changing process according to any one of claims 1 to 6.

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