Vehicle lane occupation reminding method and device, vehicle, medium and program

Abstract

The application relates to the technical field of intelligent auxiliary driving, in particular to a vehicle lane occupation reminding method and device, a vehicle, a medium and a program, wherein the method comprises the following steps: acquiring positioning data of a current vehicle, a current vehicle speed, and relative speed and relative distance between the current vehicle and a rear vehicle; generating a vehicle lane occupation result according to the positioning data, the current vehicle speed, the relative speed and the relative distance between the current vehicle and the rear vehicle; identifying a collision danger level of the current vehicle and a neighboring lane vehicle, road environment data and driver intention data; and generating reminding information of a corresponding level according to the vehicle lane occupation result, the collision danger level of the current vehicle and the neighboring lane vehicle, the road environment data, the driver intention data and the relative speed and the relative distance between the current vehicle and the rear vehicle. Therefore, the problems of high false positive rate, insufficient environment perception, single reminding mode and incapability of self-adaptive optimization of lane occupation reminding in the prior art are solved.

Description

Technical Field

[0001] This application relates to the field of intelligent assisted driving technology, and in particular to a method, device, vehicle, medium, and program for reminding vehicles to avoid lane occupancy. Background Technology

[0002] In multi-lane road environments, it is common for some vehicles to occupy the fast lane (or overtaking lane) for extended periods at low speeds. This behavior reduces lane efficiency, forces following vehicles to frequently change lanes, increases the risk of traffic conflicts and rear-end collisions, and affects overall traffic order and driving safety.

[0003] In related technologies, the vehicle's lane is identified by vehicle positioning and map matching, and the vehicle's speed is used to make a judgment: when the vehicle is in the fast lane and the speed is lower than a preset threshold, a visual or auditory prompt is triggered to remind the driver to leave the fast lane. However, the false judgment rate is high, there is a lack of active filtering for reasonable exceptions, the environmental perception dimension is single, it is difficult to assess the necessity and safety of the reminder, the reminder method is relatively rigid, and the human-computer interaction experience is poor. Summary of the Invention

[0004] This application provides a method, device, vehicle, medium, and program for reminding vehicles to occupy lanes, in order to solve the problems of high false alarm rate, insufficient environmental perception, single reminder method, and inability to adaptively optimize in related technologies.

[0005] The first aspect of this application provides a method for vehicle lane occupancy warning, comprising the following steps: acquiring the current vehicle's location data, current speed, and relative speed and distance between the current vehicle and vehicles behind it; generating a vehicle lane occupancy result based on the location data, current speed, and relative speed and distance between the current vehicle and vehicles behind it; identifying the collision risk level between the current vehicle and vehicles in adjacent lanes, road environment data, and driver intention data; and generating a warning message of a corresponding level based on the vehicle lane occupancy result, the collision risk level between the current vehicle and vehicles in adjacent lanes, road environment data, driver intention data, and relative speed and distance between the current vehicle and vehicles behind it.

[0006] Optionally, generating a vehicle lane-occupancy result based on the positioning data, the current vehicle speed, and the relative speed and relative distance between the current vehicle and the vehicle behind it includes: determining the desired speed range of the vehicle based on the positioning data of the current vehicle; if the current vehicle speed is less than the desired speed range and the duration is greater than or equal to the target duration, and the relative speed between the current vehicle and the vehicle behind it is greater than or equal to a first preset speed and the relative distance is less than or equal to the target distance, then the current vehicle is in a lane-occupancy state.

[0007] Optionally, identifying the collision risk level between the current vehicle and a vehicle in an adjacent lane includes: obtaining the lateral distance, longitudinal distance, and relative speed between the current vehicle and a target vehicle in an adjacent lane; calculating the collision duration based on the longitudinal distance and the relative speed; and determining the collision risk level between the current vehicle and a vehicle in an adjacent lane based on the lateral distance and the collision duration.

[0008] Optionally, determining the collision hazard level between the current vehicle and a vehicle in an adjacent lane based on the lateral distance and the collision duration includes: if the lateral distance is less than a first lateral distance threshold and the collision duration is less than a first duration threshold, then it is determined to be a first hazard level; if the lateral distance is less than or equal to a second lateral distance threshold and the lateral distance is greater than the first lateral distance threshold, and the collision duration is greater than or equal to the first duration threshold and less than the second duration threshold, then it is determined to be a second hazard level; if the lateral distance is greater than or equal to the second lateral distance threshold and the collision duration is greater than or equal to the second duration threshold, then it is determined to be a third hazard level; wherein, the first lateral distance threshold is less than the second lateral distance threshold, the first duration threshold is less than the second duration threshold, the first hazard level is greater than the second hazard level, and the second hazard level is greater than the third hazard level.

[0009] Optionally, the step of generating a corresponding level of alert based on the vehicle's lane occupation result, the collision risk level between the current vehicle and vehicles in adjacent lanes, road environment data, driver intention data, and the relative speed and relative distance between the current vehicle and vehicles behind includes: if the vehicle's lane occupation result indicates that the vehicle is not in a lane-occupying state, the driver intention data does not include overtaking intention or exit intention, the road environment data is not in a road congestion state or target weather state, and the collision risk level between the current vehicle and vehicles in adjacent lanes is greater than or equal to the second risk level, then a corresponding level of alert is generated based on the lane occupation duration of the vehicle's lane occupation result and the relative speed and relative distance between the current vehicle and vehicles behind; if there is at least one of the following: the vehicle's lane occupation result indicates that the vehicle is in a lane-occupying state, the driver intention data indicates overtaking intention or exit intention, the road environment data indicates a road congestion state or target weather state, and the collision risk level between the current vehicle and vehicles in adjacent lanes is greater than or equal to the second risk level, then the alert process is terminated.

[0010] Optionally, generating a corresponding level of alert information based on the lane occupation duration and the relative speed and distance between the current vehicle and the vehicle behind it includes: generating a first-level alert if the duration of the lane occupation is less than a second preset duration but greater than or equal to a target duration, the relative speed between the current vehicle and the vehicle behind it is less than or equal to a first preset speed, and the relative distance is greater than or equal to a target distance; generating a second-level alert if the duration of the lane occupation is greater than or equal to a second preset duration but less than or equal to a third preset duration, the relative speed between the current vehicle and the vehicle behind it is greater than or equal to a first preset speed but less than or equal to a second preset speed, and the relative distance is greater than or equal to a second preset distance but less than or equal to a target distance; and generating a third-level alert if the duration of the lane occupation is greater than a third preset duration, the relative speed between the current vehicle and the vehicle behind it is greater than a second preset speed, and the relative distance is less than a second preset distance; wherein the target duration is less than the second preset duration, the second preset duration is less than the third preset duration, the first preset speed is less than the second preset speed, and the target distance is greater than the second preset distance.

[0011] A second aspect of this application provides a vehicle lane occupancy warning device, comprising: an acquisition module for acquiring the current vehicle's location data, current speed, and relative speed and distance between the current vehicle and vehicles behind it; a generation module for generating a vehicle lane occupancy result based on the location data, the current speed, and the relative speed and distance between the current vehicle and vehicles behind it; an identification module for identifying the collision risk level between the current vehicle and vehicles in adjacent lanes, road environment data, and driver intention data; and a warning module for generating a warning message of a corresponding level based on the vehicle lane occupancy result, the collision risk level between the current vehicle and vehicles in adjacent lanes, road environment data, driver intention data, and the relative speed and distance between the current vehicle and vehicles behind it.

[0012] A third aspect of this application provides a vehicle, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to perform the vehicle lane occupancy reminder method as described in the above embodiments.

[0013] A fourth aspect of this application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to perform the vehicle lane occupancy reminder method as described in the above embodiments.

[0014] A fifth aspect of this application provides a computer program product, including a computer program or instructions, which, when executed, implement the vehicle lane occupancy reminder method as described in the above embodiments.

[0015] Therefore, this application has at least the following beneficial effects: This application embodiment can integrate multi-dimensional information such as positioning data, vehicle speed, rear vehicle dynamics, collision risk level of adjacent lanes, road environment, and driver intent to determine the lane occupancy status while intelligently filtering reasonable exceptions such as congestion and overtaking, significantly reducing the false alarm rate. At the same time, it assesses the safety of lane changing based on the collision risk level, avoiding issuing inappropriate suggestions when there are vehicles approaching from the right or when there is no safe space. It also generates graded progressive reminders based on the severity of lane occupancy and the urgency of vehicles behind, from mild prompts to strong warnings and introduces a dormancy mechanism, effectively improving the human-computer interaction experience. Thus, it achieves more accurate, reasonable, and humanized lane occupancy slow-moving vehicle reminders while ensuring driving safety.

[0016] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0017] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of a vehicle lane occupancy reminder method provided according to an embodiment of this application; Figure 2 This is a flowchart illustrating the specific operation steps provided in the embodiments of this application; Figure 3 This is a decision logic block diagram provided according to an embodiment of this application; Figure 4 This is a block diagram of a vehicle lane occupancy reminder device provided according to an embodiment of this application; Figure 5 This is a schematic diagram of the system structure provided according to an embodiment of this application; Figure 6 This is a structural schematic diagram of a vehicle provided according to an embodiment of this application. Detailed Implementation

[0018] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0019] A common phenomenon exists in the current highway driving environment: some vehicles travel at low speeds in the fast lane (overtaking lane), causing slow traffic in the fast lane, while the slow lane, originally designed for normal driving, effectively becomes a "fast lane." This phenomenon not only reduces the efficiency of highway traffic but also easily leads to traffic congestion and rear-end collisions.

[0020] Existing vehicles are typically only equipped with features such as cruise control and overspeed warnings, lacking a monitoring and alert mechanism for the match between lane attributes and actual driving speed. Drivers may, due to negligence or a lack of understanding of lane attributes, drive at low speeds in the fast lane for extended periods, affecting road traffic order and safety.

[0021] The existing technology relies solely on two simple conditions—"low speed" and "long duration"—for judgment, which easily triggers invalid alerts in scenarios such as congestion and overtaking, leading to a high false alarm rate. Furthermore, it lacks the ability to perceive the surrounding environment, failing to know the dynamics of the rear and adjacent lanes, and will still issue inappropriate lane-changing suggestions even in dangerous situations such as when a vehicle is approaching from the right. The interaction method is rather crude, using only a single sound prompt, which easily confuses and annoys drivers, resulting in a poor user experience. The function is isolated, not linked to the vehicle system, and operates only as an independent function, limiting its practical value. In summary, the existing solution is overly simplistic, lacking the ability to accurately assess actual conditions and provide appropriate warnings, thus leading to frequent false alarms, driver frustration, and even potential driving hazards.

[0022] Therefore, this application aims to address the technical problems of high false alarm rates, low intelligence levels, and poor user experience in existing vehicle lane occupancy warning systems. By integrating multi-dimensional information such as location data, vehicle speed, rear vehicle dynamics, collision risk levels in adjacent lanes, road environment, and driver intent, the system intelligently filters reasonable exceptions such as congestion and overtaking while determining lane occupancy status, significantly reducing the false alarm rate. Simultaneously, it assesses lane change safety based on collision risk levels, avoiding inappropriate suggestions when there are vehicles approaching from the right or when there is no safe space. Furthermore, it generates tiered, progressively increasing warnings based on the severity of lane occupancy and the urgency of rear vehicles, ranging from mild alerts to strong warnings, and introduces a dormancy mechanism, effectively improving the human-computer interaction experience. This achieves more accurate, reasonable, and user-friendly lane occupancy warnings while ensuring driving safety.

[0023] The following description, with reference to the accompanying drawings, describes a vehicle lane occupancy reminder method, device, vehicle, medium, and program according to embodiments of this application.

[0024] Specifically, Figure 1 This is a flowchart illustrating a vehicle lane occupancy reminder method provided in an embodiment of this application.

[0025] like Figure 1 As shown, the method for reminding drivers of vehicles blocking the road includes the following steps: In step S101, the current vehicle's location data, current speed, and relative speed and distance between the current vehicle and the vehicles behind it are obtained. It is understood that the embodiments of this application can obtain the current vehicle's location data, current speed, and relative speed and distance between the current vehicle and the vehicles behind it, so as to make subsequent judgments on whether the vehicle is occupying the lane, fundamentally improving the reliability and real-time performance of the lane-occupying and slow-moving reminder.

[0026] It should be noted that, as Figure 2 As shown, lane-level positioning is achieved through GPS and high-precision maps to determine whether the current lane is a fast lane, laying the foundation for lane occupancy determination. Simultaneously, real-time vehicle speed, turn signal, and pedal opening data are acquired via the CAN bus to assess the vehicle's operating status and potential lane-changing intentions. Based on this, front, rear, and side radars / cameras construct a 360° environmental perception system to identify slow-moving vehicles ahead, rapidly approaching vehicles behind, and vehicles in the right blind spot, thereby comprehensively assessing the vehicle's impact on traffic flow and the safety and feasibility of lane changes. Furthermore, a driver status monitoring system is integrated to analyze the driver's line of sight, head posture, and attention to predict whether the driver has noticed oncoming vehicles or is actively preparing to yield. Real-time traffic congestion information, road events, and average speeds across the entire road segment are accessed through the vehicle-to-everything (V2X) network and cloud platform to dynamically adjust decision-making benchmarks and identify reasonable exceptions such as congestion.

[0027] In step S102, a vehicle lane occupancy result is generated based on the positioning data, current vehicle speed, relative speed and relative distance between the current vehicle and the vehicle behind. It is understood that the embodiments of this application can accurately identify whether the current vehicle is in the fast lane based on the matching of positioning data and high-precision map, determine whether the current vehicle speed is lower than the dynamic reference speed, and determine whether there is a rapidly approaching threatening vehicle by the relative speed and relative distance of the vehicles behind. When the three conditions are met at the same time, a valid lane occupation result is generated. By introducing the joint determination of lane attributes and rear dynamics, it can accurately distinguish between lane occupation scenarios that really need intervention and reasonable situations such as congestion and overtaking, which significantly reduces the false alarm rate.

[0028] For example, on a highway with three lanes in the same direction, the leftmost lane is the fast lane (overtaking lane). This vehicle (vehicle A) is traveling in the fast lane, and a vehicle B is rapidly approaching from behind.

[0029] The vehicle location data shows that the vehicle is in the leftmost fast lane, with a current speed of 75 km / h, a road speed limit of 120 km / h, and a desired speed range of 100-120 km / h (the minimum speed limit for the fast lane is 100 km / h). The vehicle behind, vehicle B, is traveling at 110 km / h, while the vehicle itself is traveling at 75 km / h. Vehicle B is 35 km / h faster than the vehicle, so the relative speed is +35 km / h. The relative distance between vehicle B and vehicle A is 80 meters. The first preset duration is 10 seconds; the first preset speed is +20 km / h; and the first preset distance is 100 meters.

[0030] At this point, the system determines that the vehicle is in the fast lane, with a current speed of 75 km / h (below the lower limit of the desired speed range of 100 km / h) for 15 seconds (≥10 seconds), a relative speed of +35 km / h (≥ +20 km / h), and a relative distance of 80 meters (≤ 100 meters). Since all three conditions are met, the system determines that the vehicle is in a lane-occupying state and triggers the subsequent slow-down reminder process.

[0031] It should be noted that the system is only activated for in-depth analysis when all three conditions are met simultaneously: the vehicle is in the fast lane, the vehicle speed is significantly lower than the baseline speed, and a vehicle is rapidly approaching from behind and causing an impact. This step ensures the basic necessity of the alert.

[0032] In this embodiment of the application, a vehicle lane occupation result is generated based on the positioning data, the current vehicle speed, the relative speed and relative distance between the current vehicle and the vehicle behind, including: determining the desired vehicle speed range based on the positioning data of the current vehicle; if the current vehicle speed is less than the desired vehicle speed range and the duration is greater than or equal to the target duration, and the relative speed between the current vehicle and the vehicle behind is greater than or equal to a first preset speed and the relative distance is less than or equal to the target distance, then the current vehicle is in a lane occupation state.

[0033] The target duration, first preset speed, and target distance can all be set according to actual needs without specific limitations.

[0034] It is understood that the embodiments of this application can dynamically determine the expected speed range of the current road through positioning data, and combine multiple conditions such as the current speed being lower than the range for a continuous target duration, the relative speed of the following vehicle being greater than or equal to a first preset speed and the relative distance being less than or equal to the target distance to jointly determine the lane occupation status. This can effectively distinguish between lane occupation status with real safety risks and reasonable scenarios such as congestion, slow traffic, and normal overtaking, avoiding invalid triggers when there are no vehicles approaching from behind or the expected speed is low, significantly reducing the false alarm rate, and ensuring timely identification of lane occupation when the following vehicle is rapidly approaching and the vehicle is obviously slowing down, thus improving the accuracy and safety of the reminder.

[0035] It should be noted that, as Figure 2 As shown, this application first compares GPS data with a high-precision map to confirm whether the vehicle is in the fast lane. This is a prerequisite for determining lane occupancy. If the vehicle is not in the fast lane, the process returns directly without triggering any suspicion. After confirming the lane attributes, the system further evaluates the vehicle's speed: determining whether the current speed is significantly lower than the dynamic benchmark (i.e., the road speed limit minus 10 km / h, or the current lane's average traffic speed minus 15 km / h) to identify whether there is substantial low-speed behavior. If the speed is normal, the process terminates. Finally, when the vehicle simultaneously meets the conditions of being in the fast lane and traveling at a low speed, the system analyzes rear radar data to check if any vehicles have entered within 100 meters behind with a relative speed greater than 20 km / h (approaching rapidly), thus confirming whether the vehicle's low-speed lane occupancy poses a substantial threat to the traffic flow behind. Only when all three conditions are met sequentially is a preliminary suspicion of slow lane occupancy triggered. This layered judgment mechanism ensures a complete logical closed loop from lane legality and the rationality of the vehicle's driving to the authenticity of the impact from behind, effectively avoiding misjudgments when the vehicle is not in the fast lane, at normal speed, or when there are no vehicles behind.

[0036] In step S103, the collision risk level between the current vehicle and vehicles in adjacent lanes, road environment data, and driver intention data are identified. It is understood that the embodiments of this application can calculate the lateral distance, longitudinal distance and relative speed between the vehicle and vehicles in adjacent lanes in real time by integrating side radar or blind spot monitoring systems, and can accurately identify the collision risk level. At the same time, it can access real-time traffic congestion status, weather conditions and other road environment data, and use the driver monitoring system and vehicle operation signals such as turn signals, steering wheel angle, throttle opening and other vehicle operation signals to analyze the driver's overtaking, lane changing or yielding intentions, effectively assess the safety and feasibility of lane changing suggestions, and avoid issuing dangerous lane changing instructions when there is a vehicle rapidly approaching on the right or there is insufficient space for lane changing. It can also intelligently filter unnecessary reminders based on environmental factors such as congestion and bad weather and the driver's active intention to overtake, thereby significantly improving driving safety while greatly reducing invalid interference to the driver, and realizing a more reasonable, accurate and humanized lane occupancy slow-down reminder decision.

[0037] It should be noted that the collision hazard level is used to determine whether there is a rapidly approaching vehicle in the right lane or whether there is sufficient safe space to change lanes. This avoids issuing suggestions to change to the right lane in dangerous situations (such as when there is a vehicle in the blind spot), thus preventing collisions. Road environment data (such as traffic congestion and inclement weather) is used to identify objective reasons why vehicles are forced to drive at low speeds, avoiding invalid false alarms and reducing interference with the driver. Driver intent data (such as overtaking or preparing to exit) is used to identify the driver's proactive and reasonable actions, avoiding conflicts between the system and normal driving operations and improving the user experience.

[0038] Specifically, such as Figure 2As shown, after confirming a suspected lane-occupying slow-moving situation, the system sequentially checks five exemption scenarios according to a progressive logic: from the macro-external environment to subjective driving intentions, and from objective road condition constraints to the feasibility of lane-changing. First, it determines whether the road segment is congested (average speed below 60 km / h); if congestion is present, the low speed is due to objective reasons. Second, it checks if there are slow-moving vehicles blocking the way ahead (distance less than 2 seconds); if so, the vehicle is passively slowing down. Next, it analyzes whether the driver is currently or preparing to overtake (left turn signal, steering wheel torque, acceleration, and overtaking of vehicles on the right); if so, lane-occupying is a reasonable behavior. Then, it assesses safety risks such as weather, road alignment, or electronic stability program intervention to confirm whether low-speed driving is necessary. Finally, it determines whether there is a safe lane-changing window in the right lane (continuous presence of vehicles with no gap greater than 4 seconds); if not, the lane-changing suggestion is meaningless. As long as any exemption condition is met, the system determines it as a reasonable situation and terminates the alert, thus ensuring that intervention is only applied to truly unreasonable lane-occupying situations with feasible lane-changing, significantly reducing false alarms.

[0039] In this embodiment of the application, identifying the collision risk level between the current vehicle and a vehicle in an adjacent lane includes: obtaining the lateral distance, longitudinal distance, and relative speed between the current vehicle and a target vehicle in an adjacent lane; calculating the collision duration based on the longitudinal distance and relative speed; and determining the collision risk level between the current vehicle and a vehicle in an adjacent lane based on the lateral distance and the collision duration.

[0040] It is understood that the embodiments of this application can calculate the collision duration by obtaining the lateral distance, longitudinal distance and relative speed between the current vehicle and the target vehicle in the adjacent lane, and combine the lateral distance and the collision duration to comprehensively determine the collision risk level. This can quantitatively assess the real-time threat level of the vehicle in the adjacent lane to the current vehicle, thereby ensuring the safety of the driver's lane change decision, reducing the potential collision risk caused by incorrect suggestions, and significantly improving the safety and rationality of the lane occupancy slow-down reminder.

[0041] Specifically, such as Figure 2 As shown, specifically: (1) Obtain real-time traffic data from vehicle-to-everything (V2X) or cloud-based traffic information services, including the current congestion level (smooth / slow / congested / severely congested) and average vehicle speed. Alternatively, obtain speed statistics for multiple vehicles within a certain distance (e.g., 2km) ahead of this vehicle.

[0042] The system periodically (e.g., every 5 seconds) requests traffic condition information for the current road segment from the traffic cloud platform, or obtains it via broadcast from the vehicle-to-everything (V2X) roadside unit. If the level is congested or slow-moving, the system obtains the average vehicle speed for that road segment. If the average vehicle speed is below 30 km / h or the congestion level is marked in red / yellow, then a road congestion exemption is deemed valid. To prevent misjudgment due to single-point data, the average speed of multiple vehicles within 200 meters in front of this vehicle can be used for verification (by tracking multiple targets with millimeter-wave radar): if the average speed of multiple vehicles is also below 30km / h, then congestion is confirmed.

[0043] (2) Obtain the list of targets ahead output by the front millimeter-wave radar / camera. Each target contains information such as distance, relative speed, and target width to determine the current speed of the vehicle.

[0044] The system filters out the closest vehicles in the same lane as the current vehicle. If the speed of the vehicle in front is slightly higher than the current vehicle but the current vehicle is still unable to change lanes (e.g., the speed of the vehicle in front is only 2 km / h higher), it can also be considered an obstruction, and the obstruction duration is more than 1 minute. In addition, even if the initial distance between the two vehicles is large, if the vehicle in front suddenly decelerates (deceleration > 2 m / s²), it should be regarded as a potential obstruction in advance, and the warning should be terminated proactively. This mechanism can effectively distinguish whether the current vehicle is actively occupying the lane at low speed or is forced to slow down due to following the vehicle in front, thereby avoiding false alarms in reasonable following scenarios.

[0045] When determining whether a driver is overtaking or preparing to overtake, the system comprehensively detects multiple signals: if the left turn signal is on, the steering wheel torque exceeds 2 N·m for more than 0.5 seconds and the turning angle is to the left, the throttle opening increases by more than 30% within 2 seconds, and the difference between the current vehicle speed and the expected speed is greater than 10 km / h; or if the right blind spot radar detects a vehicle ahead in the adjacent lane on the right with a lower speed than the current vehicle and a relative speed greater than 5 km / h, and a lateral distance less than half the lane width, any of these conditions constitutes an overtaking intention and triggers an exemption termination warning. This mechanism accurately identifies the driver's legitimate overtaking behavior and avoids false alarms when the driver is overtaking normally.

[0046] (4) When determining whether low-speed driving is necessary due to road conditions, the system comprehensively detects the following conditions: wiper status (low or high speed for more than 3 seconds), electronic stability program activation indicator, curves with a radius of curvature of less than 250 meters or steep slopes with a gradient greater than 6% within 500 meters ahead on the high-precision map, external temperature below 2°C and humidity greater than 80% or rain, fog lights on or visibility less than 100 meters. If any of these conditions are met, a safety risk is determined, requiring low-speed driving, thus triggering the exemption termination warning. This mechanism effectively avoids unnecessary lane-occupancy warnings from the system in dangerous road conditions such as rain, snow, ice, sharp bends, steep slopes, and heavy fog, ensuring that the driver can focus on safe driving.

[0047] (5) When determining whether there is safe lane-changing space in the right lane, the system obtains the longitudinal distance, lateral offset, and relative speed of all targets in the adjacent lane through the right blind spot monitoring radar, and sorts them according to longitudinal distance. If there are vehicles in the area covered by the right rearview mirror (0-50 meters behind and 0.5-3 meters to the side), the longitudinal distance difference between each target and the vehicle is calculated to predict the gap time required for lane changing. The safe lane-changing window is defined as: there is a longitudinal gap in the right lane, the length of which is at least enough for the vehicle to travel at its current speed for more than 4 seconds, and the speed of the vehicle in front of the gap is not lower than that of the vehicle or the speed of the vehicle behind the gap is not higher than that of the vehicle. If the vehicle behind the right lane approaches rapidly at a relative speed of +30 km / h, even if there is a 4-second window, it will quickly shrink and is also considered as having no safe window. Only when there is no safe window longer than 4 seconds is it determined that lane changing is not feasible and an exemption termination reminder is triggered. This mechanism ensures that the system only suggests that the driver leave the fast lane when there are indeed safe lane-changing conditions, avoiding issuing dangerous instructions when there is heavy traffic on the right or when vehicles are approaching rapidly.

[0048] In this embodiment of the application, determining the collision hazard level between the current vehicle and a vehicle in an adjacent lane based on lateral distance and collision duration includes: if the lateral distance is less than a first lateral distance threshold and the collision duration is less than a first duration threshold, then it is determined to be a first hazard level; if the lateral distance is less than or equal to a second lateral distance threshold and the lateral distance is greater than the first lateral distance threshold, and the collision duration is greater than or equal to the first duration threshold and less than the second duration threshold, then it is determined to be a second hazard level; if the lateral distance is greater than or equal to the second lateral distance threshold and the collision duration is greater than or equal to the second duration threshold, then it is determined to be a third hazard level; wherein, the first lateral distance threshold is less than the second lateral distance threshold, the first duration threshold is less than the second duration threshold, the first hazard level is greater than the second hazard level, and the second hazard level is greater than the third hazard level.

[0049] The first horizontal distance threshold, the second horizontal distance threshold, the first duration threshold, and the second duration threshold can all be set according to actual needs, without specific limitations.

[0050] Understandably, this application embodiment can quantify the threat level of vehicles in adjacent lanes into a danger level by setting dual thresholds for lateral distance and collision duration, thus achieving a fine-grained assessment of collision risk. The smaller the lateral distance and the shorter the collision duration, the higher the danger level, which is consistent with actual driving safety perception. The tiered design, where the first lateral threshold is less than the second lateral threshold and the first time threshold is less than the second time threshold, ensures the continuity and differentiation of the level classification. Therefore, lane change suggestions can be prohibited or delayed at the first danger level (high danger), a warning can be issued at the second danger level (medium danger), and normal lane occupancy reminders can be allowed at the third danger level (low danger). This enables more reasonable decisions to be made while ensuring lane change safety, avoiding inappropriate lane change guidance when vehicles approach rapidly from the side, and significantly improving the safety and intelligence level of lane occupancy slow-down reminders.

[0051] Specifically, such as Figure 2 and 3 As shown, the system uses side radar to acquire the lateral distance and collision duration between the vehicle and a target vehicle in the adjacent lane on the right in real time. The preset first lateral distance threshold is 0.5 meters, and the second lateral distance threshold is 1.2 meters; the first duration threshold is 3 seconds, and the second duration threshold is 6 seconds. When the detected lateral distance is less than 0.5 meters and the collision duration is less than 3 seconds, it is classified as the first danger level (high danger), at which point the vehicle on the right is very close and a collision with the vehicle is likely to occur within a very short time.

[0052] When the lateral distance is between 0.5 meters and 1.2 meters (inclusive but greater than 0.5 meters), and the collision duration is between 3 seconds and 6 seconds (inclusive but greater than or equal to 3 seconds), it is judged as the second danger level (medium danger), indicating that although the vehicle on the right is not close to the other vehicle, there is a certain risk of collision.

[0053] When the lateral distance is greater than or equal to 1.2 meters and the collision duration is greater than or equal to 6 seconds, it is classified as Level 3 (low risk), indicating that there is ample safety space in the right lane or no significant threat. Through this three-tiered risk classification, the system can accurately adjust its warning strategy based on actual lateral risks, avoiding misleading drivers in dangerous lane-changing scenarios while ensuring that lane-occupancy slow-down warnings are issued normally under safe conditions.

[0054] In step S104, a corresponding level of warning information is generated based on the vehicle lane occupancy result, the collision risk level between the current vehicle and vehicles in adjacent lanes, road environment data, driver intention data, and the relative speed and relative distance between the current vehicle and vehicles behind.

[0055] It is understood that the embodiments of this application can dynamically generate graded reminder information that matches the current risk level by integrating multi-dimensional information such as vehicle lane occupation results, collision risk level of adjacent lanes, road environment data, driver intention data, and relative speed and distance of vehicles behind. This effectively avoids false alarms or missed alarms caused by single-dimensional judgment, ensuring that the reminders do not excessively interfere with the driver, and provide timely, clear and safety-based notifications when intervention is truly needed. This significantly improves the accuracy, safety and user experience of the lane occupation and slow-moving reminder system.

[0056] Specifically, such as Figure 2 and 3 As shown, in one specific embodiment, the system first determines the vehicle's lane occupation result as "in lane occupation state" based on positioning data, current vehicle speed and information of vehicles behind (i.e., located in the fast lane, the vehicle speed is lower than the dynamic reference and a vehicle is rapidly approaching from behind).

[0057] Subsequently, the following auxiliary information is acquired in parallel: the collision risk level between the vehicle and the vehicle in the adjacent lane on the right is calculated using side radar (e.g., currently at the second risk level, indicating there is a vehicle on the right but there is still a safe distance); the current road congestion index is determined to be smooth using cloud traffic data; the weather is confirmed to be sunny and the road surface to be dry using rain sensors and electronic stability program status; and the driver's status monitoring and CAN bus detect that the left turn signal is not activated, there is no intention to overtake on the steering wheel, and the accelerator pedal is opened smoothly. Under these circumstances, the system determines that there are no exemption conditions and enters the graded reminder generation process.

[0058] If the lane occupation has lasted for 25 seconds (between the first preset duration of 10 seconds and the second preset duration of 30 seconds), and the relative speed of the vehicle behind is +25 km / h and the relative distance is 75 meters (in the medium-emergency range), the system generates a second-level warning message: a yellow icon flashes continuously on the instrument panel, and a voice announcement says, "You are driving slowly in the fast lane. There is a vehicle approaching from behind. It is recommended to move to the right lane when it is safe to do so." If the driver still does not respond, and the lane occupation time exceeds 2 minutes and the relative speed behind increases to +40 km / h and the distance decreases to 40 meters, the warning is upgraded to a third-level warning: the instrument icon flashes red rapidly, the head-up display shows "Do not occupy the overtaking lane," and a voice prompt says, "Please give way in the fast lane immediately," accompanied by a rapid warning tone; after one warning, the system enters a 5-minute sleep period. Conversely, if a collision hazard level of Level 1 (lateral distance < 0.5 meters and collision duration < 3 seconds) is detected before generating a warning, the system will immediately terminate the lane change suggestion regardless of the lane occupancy status, and instead issue a safety warning of "Danger on the right, do not change lanes" while maintaining Level 1 visual warning, thus ensuring that the warning behavior always prioritizes driving safety.

[0059] In this embodiment, a corresponding level of alert is generated based on the vehicle's lane occupation result, the collision risk level between the current vehicle and vehicles in adjacent lanes, road environment data, driver intention data, and the relative speed and relative distance between the current vehicle and vehicles behind. This includes: if the vehicle's lane occupation result indicates the vehicle is not in a lane-occupying state, the driver intention data does not include overtaking or exit intentions, the road environment data is not in a congested or non-target weather condition, and the collision risk level between the current vehicle and vehicles in adjacent lanes is greater than or equal to the second risk level, then a corresponding level of alert is generated based on the lane occupation duration and the relative speed and relative distance between the current vehicle and vehicles behind; if there is at least one of the following: the vehicle's lane occupation result indicates the vehicle is in a lane-occupying state, the driver intention data indicates overtaking or exit intentions, the road environment data indicates a congested or target weather condition, and the collision risk level between the current vehicle and vehicles in adjacent lanes is greater than or equal to the second risk level, then the alert process is terminated.

[0060] It is understood that the embodiments of this application can comprehensively judge the result of a vehicle occupying a lane by combining the driver's intention, road environment, collision risk level of adjacent lanes, and the dynamics of vehicles behind. When the lane occupancy status is established and there are no exceptions, the system can generate graded reminders based on the duration of lane occupancy and the proximity of vehicles behind. However, when there are any exceptions such as the driver overtaking or preparing to exit, the road being congested or in bad weather, or the collision risk level of adjacent lanes reaching the medium level or above, the reminder process is automatically terminated. This accurately distinguishes between scenarios that truly require intervention and situations where lane occupancy should be temporarily suspended, effectively avoiding invalid or dangerous reminders caused by congestion, overtaking, or side hazards. Under the premise of ensuring driving safety, it significantly reduces the false alarm rate and driver interference, and achieves a more intelligent, safe, and user-friendly lane occupancy and slow-moving reminder.

[0061] Specifically, in one embodiment, the system first determines that the vehicle is "in a lane-occupying state" (i.e., located in the fast lane, with its speed below the dynamic baseline and a vehicle rapidly approaching from behind). Then, it comprehensively detects various exception conditions: confirming through driver status monitoring and the CAN bus that the driver currently has no intention to overtake (left turn signal not activated, no active steering wheel, smooth throttle) and no intention to exit the exit; confirming through cloud traffic data and rain sensors that the current road segment is clear and the weather is sunny (not congested, not in severe weather); and calculating through side radar that the collision risk level of the adjacent lane on the right is level three (low risk, lateral distance greater than 1.2 meters and collision duration greater than 6 seconds). Since there are no exemption conditions (i.e., no special driver intention, normal road conditions, low lateral risk level), the system enters a graded alert process: based on the lane-occupying duration (reaching 20 seconds) and the relative speed (+25 km / h) and relative distance (80 meters) of the vehicle behind, a level two alert is generated, including voice announcement and continuous visual prompts. Conversely, if any of the above exceptions are met—for example, if the system detects that the driver has activated the left turn signal and is accelerating (indicating overtaking), or if the road is congested, or if the right-side collision risk level is level two or higher—then the system will immediately terminate the alert process regardless of whether the lane occupancy result is valid, to avoid unnecessary or dangerous interference to the driver. Through this comprehensive decision-making mechanism, the system can accurately distinguish between scenarios that truly require intervention and those with reasonable exemptions, significantly improving the rationality and safety of the alerts.

[0062] In this embodiment, a corresponding level of alert information is generated based on the duration of lane occupation and the relative speed and distance between the current vehicle and the vehicle behind it. This includes: generating a first-level alert if the duration of lane occupation is less than a second preset duration but greater than or equal to a target duration, the relative speed between the current vehicle and the vehicle behind it is less than or equal to a first preset speed, and the relative distance is greater than or equal to a target distance; generating a second-level alert if the duration of lane occupation is greater than or equal to a second preset duration but less than or equal to a third preset duration, the relative speed between the current vehicle and the vehicle behind it is greater than or equal to a first preset speed but less than or equal to a second preset speed, and the relative distance is greater than or equal to a second preset distance but less than or equal to a target distance; and generating a third-level alert if the duration of lane occupation is greater than a third preset duration, the relative speed between the current vehicle and the vehicle behind it is greater than a second preset speed, and the relative distance is less than a second preset distance. The target duration is less than the second preset duration, the second preset duration is less than the third preset duration, the first preset speed is less than the second preset speed, and the target distance is greater than the second preset distance.

[0063] The target duration, second preset duration, third preset duration, first preset speed, second preset speed, target distance, and second preset distance can all be set according to actual needs without specific limitations.

[0064] It is understood that the embodiments of this application can achieve a progressively stronger reminder strategy from level one to level three by setting multi-level thresholds for the duration of lane occupation and the relative speed and distance of vehicles behind (the longer the lane occupation duration, the greater the relative speed behind, and the closer the distance, the higher the reminder level). This ensures that the reminder intensity is precisely matched with the severity of the lane occupation and the risk of rear collision. This avoids driver frustration and fatigue caused by frequent, high-intensity invalid alarms, while providing timely and powerful warnings in scenarios where intervention is truly necessary. Thus, while ensuring driving safety, it significantly improves the rationality of human-computer interaction and user acceptance.

[0065] It should be noted that the system employs a three-tiered progressive alert strategy: The first-level alert, triggered for the first time or in minor situations, displays a gentle, flashing yellow "Vehicle moving to the right" icon on the instrument panel or head-up display, accompanied by a short, non-urgent alert tone. The head-up display brightness automatically adjusts according to ambient light (500-12000 nits). If the status remains unchanged after 5 seconds, the alert is upgraded. The second-level alert, triggered when the vehicle continues to obstruct the right lane for more than 30 seconds or when the impact from behind worsens, involves a continuous flashing of the icon on the instrument panel or head-up display, accompanied by a clear, neutral female voice announcement: "You are..." "Drive slowly in the fast lane, there is a vehicle approaching from behind. It is recommended to move to the right lane when it is safe." If this message is ignored for 5 seconds, the alert level is upgraded. For Level 3 alerts, if the driver ignores the message for an extended period (more than 2 minutes without moving), the instrument panel icon turns red and flashes rapidly at a frequency of 2Hz. The head-up display shows "Do not occupy the overtaking lane," and emits a more urgent "beep beep" sound with a stronger emphasis, "Please leave the fast lane immediately." If the driver still does not respond, the system enters a dormant period after this strong warning (e.g., it will not repeat the same warning for 5 minutes) to avoid excessive interference. This tiered mechanism ensures the necessary warning intensity while also considering the driver's experience and safety.

[0066] Specifically, in one embodiment, the system presets a target duration of 5 seconds (after the first trigger, continuous lane occupation for 5 seconds constitutes a Level 1 alert threshold), a second preset duration of 30 seconds, and a third preset duration of 120 seconds (2 minutes); a first preset speed of +15 km / h and a second preset speed of +30 km / h; a target distance of 100 meters and a second preset distance of 50 meters. When the duration of lane occupation reaches 5 seconds but is less than 30 seconds, and the relative speed of vehicles behind does not exceed 15 km / h and the relative distance is greater than or equal to 100 meters, a Level 1 alert is generated: a "Vehicle moving to the right" icon flashes gently in yellow on the dashboard, accompanied by a short warning sound, lasting for 5 seconds.

[0067] When the duration of the lane occupancy is between 30 and 120 seconds (inclusive), and the relative speed behind is between 15 km / h and 30 km / h, and the relative distance is between 50 meters and 100 meters (inclusive), a second-level warning message is generated: a visual icon flashes continuously, and a voice announcement is made saying "You are driving slowly in the fast lane, there is a vehicle approaching from behind. It is recommended to change to the right lane when it is safe to do so," which lasts for 5 seconds.

[0068] When the lane occupancy lasts for more than 120 seconds, and the relative speed behind is greater than 30 km / h and the relative distance is less than 50 meters, a third-level warning message is generated: the instrument panel icon flashes red rapidly (2Hz), the head-up display shows "Do not occupy the overtaking lane," accompanied by a rapid "beep beep" sound and a stressed voice prompt "Please give way in the fast lane immediately." After one warning, the system enters a 5-minute sleep period to avoid continuous disturbance. Through the above three-level tiered warning system based on the duration of lane occupancy and the degree of threat from behind, a smooth transition from mild notification to strong warning is achieved, giving drivers reasonable reaction time while providing clear warnings in emergency situations, and avoiding excessive disturbance.

[0069] In addition, after the reminder event ends, the vehicle terminal will package and upload the de-identified data (including event identifier, road sign, traffic density, trigger time, duration, whether the driver has left the vehicle and whether there is a false alarm, etc., excluding personally identifiable information) to the cloud. After collecting massive amounts of data, the cloud will periodically (e.g., weekly) retrain the congestion judgment and minimum recommended speed, and silently push the optimized model parameters and judgment thresholds back to the vehicle terminal through wireless upgrades, so as to realize the continuous iteration and personalized adaptation of decision rules.

[0070] The vehicle lane occupancy warning method proposed in this application integrates multi-dimensional information such as location data, vehicle speed, rear vehicle dynamics, collision risk level of adjacent lanes, road environment, and driver intent. While judging the lane occupancy status, it intelligently filters reasonable exceptions such as congestion and overtaking, significantly reducing the false alarm rate. At the same time, it assesses the safety of lane changing based on the collision risk level, avoiding issuing inappropriate suggestions when there are vehicles approaching from the right or when there is no safe space. It also generates graded progressive warnings based on the severity of lane occupancy and the urgency of rear vehicles, from mild prompts to strong warnings and introduces a dormancy mechanism, effectively improving the human-computer interaction experience. Thus, it achieves more accurate, reasonable, and humanized lane occupancy warnings while ensuring driving safety.

[0071] Next, the vehicle lane occupancy reminder device according to the embodiments of this application is described with reference to the accompanying drawings.

[0072] Figure 4 This is a block diagram of a vehicle lane occupancy reminder device according to an embodiment of this application.

[0073] like Figure 4 As shown, the vehicle lane occupancy warning device 10 includes: an acquisition module 100, a generation module 200, an identification module 300, and a warning module 400.

[0074] The acquisition module 100 is used to acquire the current vehicle's location data, current speed, and relative speed and distance between the current vehicle and vehicles behind it; the generation module 200 is used to generate a vehicle lane occupation result based on the location data, current speed, and relative speed and distance between the current vehicle and vehicles behind it; the identification module 300 is used to identify the collision risk level between the current vehicle and vehicles in adjacent lanes, road environment data, and driver intention data; and the reminder module 400 is used to generate a corresponding level of reminder information based on the vehicle lane occupation result, the collision risk level between the current vehicle and vehicles in adjacent lanes, road environment data, driver intention data, and relative speed and distance between the current vehicle and vehicles behind it.

[0075] Specifically, such as Figure 5 As shown, this application also includes: a perception layer, a decision-making layer, an execution layer, and an optimization layer. The perception layer involves initializing various sensors and modules after vehicle startup. External environment perception uses front, rear, and side cameras / millimeter-wave radar to collect real-time target data in front of, behind, and adjacent lanes of the vehicle. The positioning and mapping module uses GPS and high-precision maps to achieve lane-level positioning and identify whether the current lane is a fast lane. Vehicle status perception obtains vehicle speed, turn signals, accelerator / brake opening, etc., via the CAN bus. Driver status perception analyzes the driver's line of sight and head posture using a DMS camera. External data access obtains real-time traffic congestion information and average vehicle speed for road segments through the vehicle network and cloud platform. All raw data streams are uniformly sent to the decision-making layer.

[0076] Decision Layer: The data fusion and preprocessing center performs spatiotemporal alignment and filtering on multi-source heterogeneous data, outputting fused structured information. The hierarchical intelligent decision engine executes three layers of algorithms sequentially: The first layer determines whether three necessary conditions are met simultaneously: being in the fast lane, the vehicle's speed being significantly lower than the dynamic baseline, and a vehicle rapidly approaching from behind. If met, the second layer initiates exception analysis, sequentially checking five types of exemption conditions: road congestion, obstruction by a slow vehicle ahead, driver's overtaking intention, road condition restrictions, and feasibility of changing lanes to the right. If no exemption exists, the third layer generates a final decision on unreasonable lane occupation and determines the alert level (Level 1, 2, or 3) based on the duration of lane occupation and the degree of threat from behind (relative speed and distance), which is then handed over to the alert strategy controller to output specific control instructions.

[0077] Execution Layer: The alert strategy controller drives the visual alert system (displaying icons and text on the dashboard / HUD), the voice alert system (playing synthesized speech through speakers), and the tactile alert system (steering wheel or seat vibration, optional) based on the decision results. Level 1 alerts consist of a gentle flashing yellow icon and a short alert sound; Level 2 alerts consist of a continuous flashing icon and a neutral voice suggestion; Level 3 alerts consist of a highlighted red icon, a rapid alarm sound, and an emphasized tone, and then enter a dormant period after a strong alert to avoid excessive interference.

[0078] Optimization Layer: After each alert event, the vehicle terminal uploads anonymized data (event ID, road ID, traffic density, trigger time, duration, whether the driver left the vehicle, whether there was a false alarm, etc.) to the driving behavior data warehouse. The machine learning and model optimization module periodically (e.g., weekly) retrains the congestion judgment model and the minimum suggested speed model, optimizes the judgment thresholds (e.g., speed difference, time delay, etc.) and personalized adaptation parameters, and silently pushes updates to the decision-making layer via wireless upgrades, achieving closed-loop self-learning and continuous iteration of the system.

[0079] The vehicle lane occupancy warning device proposed in this application integrates multi-dimensional information such as positioning data, vehicle speed, rear vehicle dynamics, collision risk level of adjacent lanes, road environment, and driver intent. While judging the lane occupancy status, it intelligently filters reasonable exceptions such as congestion and overtaking, significantly reducing the false alarm rate. At the same time, it assesses the safety of lane changing based on the collision risk level, avoiding issuing inappropriate suggestions when there are vehicles approaching from the right or when there is no safe space. It also generates graded progressive warnings based on the severity of lane occupancy and the urgency of rear vehicles, from mild prompts to strong warnings and introduces a dormancy mechanism, effectively improving the human-computer interaction experience. Thus, it achieves more accurate, reasonable, and humanized lane occupancy warnings while ensuring driving safety.

[0080] Figure 6 A schematic diagram of the structure of a vehicle provided in an embodiment of this application. The vehicle may include: The memory 601, the processor 602, and the computer program stored on the memory 601 and capable of running on the processor 602.

[0081] When the processor 602 executes the program, it implements the vehicle lane occupancy reminder method provided in the above embodiments.

[0082] Furthermore, the vehicle also includes: Communication interface 603 is used for communication between memory 601 and processor 602.

[0083] The memory 601 is used to store computer programs that can run on the processor 602.

[0084] The memory 601 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0085] If the memory 601, processor 602, and communication interface 603 are implemented independently, then the communication interface 603, memory 601, and processor 602 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 6 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0086] Optionally, in a specific implementation, if the memory 601, processor 602, and communication interface 603 are integrated on a single chip, then the memory 601, processor 602, and communication interface 603 can communicate with each other through an internal interface.

[0087] The processor 602 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0088] This application also provides a computer-readable storage medium storing a computer program or instructions thereon, which, when executed by a processor, implements the vehicle lane occupancy reminder method described above.

[0089] This application also provides a computer program product, including a computer program or instructions, which, when executed, implement the above-described vehicle lane occupancy reminder method.

[0090] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0091] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0092] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0093] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or more of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0094] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

Claims

1. A method for reminding drivers of vehicles occupying lanes, characterized in that, Includes the following steps: Obtain the current vehicle's location data, current speed, and relative speed and distance between the current vehicle and vehicles behind it; Based on the location data, the current vehicle speed, and the relative speed and relative distance between the current vehicle and the vehicles behind, a vehicle lane occupation result is generated; Identify the collision risk level between the current vehicle and vehicles in adjacent lanes, road environment data, and driver intention data; Based on the vehicle's lane occupancy result, the collision risk level between the current vehicle and vehicles in adjacent lanes, road environment data, driver intention data, and the relative speed and relative distance between the current vehicle and vehicles behind, a corresponding level of warning information is generated.

2. The vehicle lane occupancy reminder method according to claim 1, characterized in that, The step of generating a vehicle lane occupancy result based on the positioning data, the current vehicle speed, and the relative speed and relative distance between the current vehicle and the vehicles behind includes: The desired speed range of the vehicle is determined based on the current vehicle location data; If the current vehicle speed is less than the expected speed range and the duration is greater than or equal to the target duration, and the relative speed between the current vehicle and the vehicle behind is greater than or equal to the first preset speed and the relative distance is less than or equal to the target distance, then the current vehicle is in a lane-occupying state.

3. The vehicle lane-occupancy reminder method according to claim 2, characterized in that, The method of identifying the collision risk level between the current vehicle and vehicles in adjacent lanes includes: Obtain the lateral distance, longitudinal distance, and relative speed between the current vehicle and the target vehicle in the adjacent lane; The collision duration is calculated based on the longitudinal distance and the relative speed, and the collision hazard level between the current vehicle and the vehicle in the adjacent lane is determined based on the lateral distance and the collision duration.

4. The vehicle lane-occupancy reminder method according to claim 3, characterized in that, The step of determining the collision risk level between the current vehicle and vehicles in adjacent lanes based on the lateral distance and the collision duration includes: If the lateral distance is less than a first lateral distance threshold and the collision duration is less than a first duration threshold, then it is determined to be a first danger level; If the lateral distance is less than or equal to the second lateral distance threshold and the lateral distance is greater than the first lateral distance threshold, and the collision duration is greater than or equal to the first duration threshold and less than the second duration threshold, then it is determined to be the second danger level; If the lateral distance is greater than or equal to the second lateral distance threshold and the collision duration is greater than or equal to the second duration threshold, then it is determined to be the third danger level; wherein, the first lateral distance threshold is less than the second lateral distance threshold, the first duration threshold is less than the second duration threshold, the first danger level of the first lateral distance threshold is greater than the second danger level, and the second danger level is greater than the third danger level.

5. The vehicle lane-occupancy reminder method according to claim 4, characterized in that, The method of generating a corresponding level of alert based on the vehicle's lane occupancy result, the collision risk level between the current vehicle and vehicles in adjacent lanes, road environment data, driver intention data, and the relative speed and relative distance between the current vehicle and vehicles behind includes: If the vehicle lane occupation result is that the vehicle is not in a lane occupation state, the driver intention data does not include overtaking intention or exit intention, the road environment data is not in a road congestion state or not in the target weather state, and the collision risk level between the current vehicle and the vehicle in the adjacent lane is greater than or equal to the second risk level, then a corresponding level of reminder is generated based on the lane occupation duration of the vehicle lane occupation result and the relative speed and relative distance between the current vehicle and the vehicle behind. If the vehicle is in a lane-occupying state, the driver's intention data is overtaking or exiting the exit, the road environment data is traffic congestion or target weather conditions, and the collision risk level between the current vehicle and the vehicle in the adjacent lane is greater than or equal to at least the second risk level, then the reminder process will be terminated.

6. The vehicle lane-occupancy reminder method according to claim 5, characterized in that, The process of generating corresponding alert information based on the duration of lane occupation and the relative speed and distance between the current vehicle and the vehicles behind it includes: If the duration of the road occupancy is less than the second preset duration but greater than or equal to the target duration, the relative speed between the current vehicle and the vehicle behind is less than or equal to the first preset speed, and the relative distance is greater than or equal to the target distance, then a first-level reminder message is generated. If the duration of the road occupancy state is greater than or equal to the second preset duration and less than or equal to the third preset duration, the relative speed between the current vehicle and the vehicle behind is greater than or equal to the first preset speed and less than or equal to the second preset speed, and the relative distance is greater than or equal to the second preset distance and less than or equal to the target distance, then a second-level reminder message is generated. If the duration of the road occupancy state is greater than the third preset duration, and the relative speed between the current vehicle and the vehicle behind it is greater than the second preset speed and the relative distance is less than the second preset distance, then a third-level reminder message will be generated. Among them, the target duration is less than the second preset duration, the second preset duration is less than the third preset duration, the first preset speed is less than the second preset speed, and the target distance is greater than the second preset distance.

7. A vehicle lane-occupancy warning device, characterized in that, include: The acquisition module is used to acquire the current vehicle's location data, current speed, and relative speed and distance between the current vehicle and vehicles behind it. The generation module is used to generate a vehicle lane occupation result based on the positioning data, the current vehicle speed, and the relative speed and relative distance between the current vehicle and the vehicle behind it. The identification module is used to identify the collision risk level between the current vehicle and vehicles in adjacent lanes, road environment data, and driver intention data; The reminder module is used to generate reminder information of corresponding levels based on the vehicle's lane occupation result, the collision risk level between the current vehicle and vehicles in adjacent lanes, road environment data, driver intention data, and the relative speed and relative distance between the current vehicle and vehicles behind.

8. A vehicle, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the vehicle lane occupancy warning method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed by the processor, they are used to implement the vehicle lane occupancy reminder method as described in any one of claims 1-6.

10. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed, they implement the vehicle lane occupancy reminder method as described in any one of claims 1-6.

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