Intersection yawing early warning method, device, equipment, storage medium and program product

Abstract

The application provides a kind of intersection deviation early warning method, device, equipment, storage medium and program product, it is related to vehicle driving technical field.The method comprises: based on the navigation path of target vehicle, the lane information of import lane of first navigation intersection in front is acquired;Based on lane information, the deviation state of target vehicle is determined;If target vehicle deviates, then based on its speed, relative distance and lateral offset distance, deviation early warning factor is determined;When deviation early warning factor is greater than deviation early warning trigger threshold, trigger deviation early warning.The application obtains the lane information of import lane in front in advance, realizes the fine monitoring of vehicle driving state, not only can accurately judge the deviation state of vehicle, but also obtains deviation early warning factor by comprehensively quantifying multi-source information, and judges whether to trigger deviation early warning based on deviation early warning factor, can trigger early warning in time before vehicle actually deviates, so as to significantly enhance the early warning ability of intersection deviation.

Description

Technical Field

[0001] This application relates to the field of vehicle driving technology, and in particular to a method, device, equipment, storage medium, and program product for crossroads veergence warning. Background Technology

[0002] In recent years, with the increasing complexity of road networks and the continuous increase in the number of vehicles, route navigation has faced increasingly severe challenges. In particular, when navigation enters an intersection, it often deviates from the intended path due to selecting the wrong lane. This not only affects the driving experience but may also affect the efficiency of intersection traffic, leading to traffic congestion and even traffic accidents.

[0003] In related technologies, navigation systems typically output deviation alerts after a vehicle deviates from its course when entering an intersection, but they lack the ability to provide early warnings of deviations from intersections. Summary of the Invention

[0004] This application provides a method, device, equipment, storage medium, and program product for early warning of road deviation at intersections, in order to enhance the early warning capability of road deviation at intersections.

[0005] Firstly, this application provides a method for early warning of road deviation at intersections, including:

[0006] Based on the navigation path of the target vehicle, obtain the lane information of the entrance lane of the first navigation intersection ahead;

[0007] Based on lane information, the deviation status of the target vehicle is determined. The deviation status includes whether a deviation has occurred, as well as the deviation direction and lateral offset distance when a deviation occurs.

[0008] If the target vehicle deviates, the yaw warning factor of the target vehicle is determined based on the target vehicle's speed, relative distance, and lateral deviation distance. The relative distance is the distance from the target vehicle to the starting point of the approach lane.

[0009] If the yaw warning factor is greater than the preset yaw warning trigger threshold, a yaw warning will be triggered for the target vehicle.

[0010] In one possible implementation, before determining the deviation state of the target vehicle based on lane information, the method further includes: determining the relative distance between the target vehicle and the starting point of the approach lane based on lane information; if the relative distance is less than the yaw check distance threshold, then determining the deviation state of the target vehicle based on lane information.

[0011] In one possible implementation, the yaw warning factor for the target vehicle is determined based on the target vehicle's speed, relative distance, and lateral offset distance, including: determining the target vehicle's safety barrier distance based on the speed; subtracting the relative distance from the safety barrier distance to obtain a first distance difference; taking the maximum value between the first distance difference and 0 as the remaining safe distance between the target vehicle and the approach lane; adding half the lane width of the approach lane to the remaining safe distance to obtain a reference distance; and determining the ratio of the lateral offset distance to the reference distance as the yaw warning factor.

[0012] In one possible implementation, determining the deviation state of the target vehicle based on lane information includes: determining the target boundary lane in the same direction as the approach lane at the first navigation intersection ahead based on lane information; and determining the deviation state of the target vehicle based on the position coordinates of the target vehicle and the lane information of the target boundary lane.

[0013] In one possible implementation, based on lane information, the target boundary lane in the first navigation intersection ahead that is in the same direction as the approach lane is determined, including: taking the approach lane as the starting lane, recursively searching for lanes in the first navigation intersection ahead that have the same lane turning type as the approach lane along the target direction, until the lane turning type is different from the lane turning type of the approach lane, and then stopping the recursive search, and determining the last lane with the same lane turning type as the approach lane as the target boundary lane.

[0014] In one possible implementation, determining the deviation state of the target vehicle based on its position coordinates and lane information of the target boundary lane includes: acquiring two reference coordinate points on the centerline of the target boundary lane; determining the deviation direction of the target vehicle based on the vector relationship formed by the position coordinates of the target vehicle and the two reference coordinate points; determining the lateral distance between the target vehicle and the centerline of the target boundary lane using operations between the position coordinates and the vector formed by the two reference coordinate points; subtracting half the lane width of the target boundary lane from the lateral distance to obtain a second distance difference; taking the maximum value between the second distance difference and 0 as the lateral offset distance; and determining whether the target vehicle has deviated based on the sign of the lateral offset distance.

[0015] In one possible implementation, the yaw warning includes deviation from bearing, lateral offset distance, and relative distance. When the yaw warning factor is greater than a preset yaw warning trigger threshold, a yaw warning is triggered for the target vehicle, including: determining the threshold difference between the yaw warning factor and the yaw warning trigger threshold; and triggering a yaw warning of the corresponding level based on the range to which the threshold difference belongs.

[0016] Secondly, this application provides a road descent warning device, comprising:

[0017] The acquisition module is used to obtain lane information of the entrance lane of the first navigation intersection ahead, based on the navigation path of the target vehicle.

[0018] The first determining module is used to determine the deviation status of the target vehicle based on lane information. The deviation status includes whether a deviation has occurred, as well as the deviation direction and lateral offset distance when a deviation occurs.

[0019] The second determining module is used to determine the yaw warning factor of the target vehicle based on the target vehicle's driving speed, relative distance, and lateral deviation distance when the target vehicle deviates. The relative distance is the distance from the target vehicle to the starting point of the approach lane.

[0020] The yaw warning module is used to trigger a yaw warning for the target vehicle when the yaw warning factor is greater than the preset yaw warning trigger threshold.

[0021] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0022] Memory is used to store instructions executed by the computer;

[0023] A processor for executing computer-executable instructions stored in memory to implement the method described in any of the first aspects.

[0024] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed, are used to implement the method described in any of the first aspects.

[0025] Fifthly, this application provides a computer program product, including a computer program that, when executed, implements the method described in any of the first aspects.

[0026] The intersection veergence warning method, device, equipment, storage medium, and program product provided in this application obtain lane information of the approach lane of the first navigation intersection ahead based on the navigation path of the target vehicle; and determine the deviation status of the target vehicle based on the lane information, including whether a deviation has occurred, and the deviation direction and lateral offset distance when a deviation occurs; if the target vehicle deviates, a veergence warning factor is determined based on the target vehicle's driving speed, relative distance, and lateral offset distance, where the relative distance is the distance from the target vehicle to the starting point of the approach lane; furthermore, if the veergence warning factor is greater than a preset veergence warning trigger threshold, a veergence warning is triggered for the target vehicle. In this process, by obtaining lane information of the first approach lane at the navigation intersection ahead based on the target vehicle's navigation path, refined monitoring of the vehicle's driving status is achieved. This not only accurately determines whether the vehicle has deviated, and the direction and lateral deviation distance, but also obtains a yaw warning factor by comprehensively quantifying driving speed, relative distance, and lateral deviation distance. Based on the yaw warning factor, it further determines whether to trigger a yaw warning. This multi-dimensional parameter fusion warning mechanism significantly improves the predictive ability of yaw risk, and can trigger a warning in time before the vehicle actually deviates. It effectively solves the problem of the lag in traditional navigation systems, which can only provide reminders after the fact. This significantly enhances the early warning capability of intersection yaw, thereby effectively reducing the risk of yaw caused by incorrect lane selection. It is of great significance for improving intersection traffic efficiency, reducing traffic congestion and accident rates, and providing drivers with more forward-looking safety protection. Attached Figure Description

[0027] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0028] Figure 1 A flowchart illustrating an intersection velocity warning method provided as an exemplary embodiment of this application;

[0029] Figure 2 A schematic diagram of the deviation state provided for an exemplary embodiment of this application;

[0030] Figure 3 Another schematic diagram of the intersection veergence warning method provided as an exemplary embodiment of this application;

[0031] Figure 4 A schematic diagram of a road yaw warning device provided as an exemplary embodiment of this application;

[0032] Figure 5 A schematic diagram of the structure of an electronic device provided as an exemplary embodiment of this application.

[0033] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0034] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0035] The terms “first,” “second,” etc., used in the specification and claims of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented, for example, in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, products, or apparatus.

[0036] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0037] In related technologies, traditional navigation systems typically issue deviation warnings after a vehicle deviates from its course when entering an intersection, but they cannot predict risks before deviation occurs. This lack of early warning capability for deviations from intersections results in a warning window that lags behind the optimal adjustment period, affecting not only the driving experience but also the efficiency of intersection traffic flow, leading to traffic congestion and even traffic accidents.

[0038] To address the aforementioned issues, this application provides an intersection deviation warning scheme. By real-time analysis of the target vehicle's navigation path and loading lane information from the first intersection's approach lane, combined with high-precision positioning, the scheme dynamically determines the target vehicle's deviation status. Upon detecting a deviation, it constructs a deviation warning factor integrating spatiotemporal and speed features, incorporating multi-source information. Furthermore, when the deviation warning factor exceeds a threshold, a deviation warning is triggered for the target vehicle, achieving proactive safety intervention from "post-deviation alert" to "pre-deviation prediction." This significantly enhances the early warning capability for intersection deviations, effectively reducing the risk of deviations caused by lane selection errors. This is of great significance for improving intersection traffic efficiency, reducing traffic congestion and accident rates, and providing drivers with more proactive safety assurance.

[0039] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0040] Figure 1 A schematic flowchart of an intersection veergence warning method provided as an exemplary embodiment of this application is shown. Figure 1 As shown, the deviation warning method at this intersection includes the following steps:

[0041] S101. Based on the navigation path of the target vehicle, obtain the lane information of the entrance lane of the first navigation intersection ahead.

[0042] For example, the navigation system's application programming interface (API) is called to obtain the target vehicle's currently planned global path, such as a Global Positioning System (GPS) trajectory or a high-precision map path. The first navigation intersection ahead of the path, such as an intersection or ramp entrance, is extracted, and the left-turn lane at that intersection is extracted and denoted as cross_enter_lane. If there are two parallel left-turn lanes, such as left-turn lane 1 and left-turn lane 2, one of them, such as left-turn lane 1, is randomly selected as the entrance lane, and its lane width, lane centerline coordinates, and lane identifier (ID) and other attribute information are recorded.

[0043] S102. Based on lane information, determine the deviation status of the target vehicle. The deviation status includes whether a deviation has occurred, as well as the deviation direction and lateral offset distance when a deviation occurs.

[0044] In some embodiments, determining the deviation state of the target vehicle based on lane information includes: determining the target boundary lane in the same direction as the approach lane at the first navigation intersection ahead based on lane information; and determining the deviation state of the target vehicle based on the position coordinates of the target vehicle and the lane information of the target boundary lane.

[0045] For example, the deviation direction is determined by the positional relationship between the current position of the target vehicle and the center line of the target boundary lane, such as the deviation direction being "left" or "right"; the lateral offset distance is determined based on the vertical distance from the target vehicle to the center line of the target boundary lane; and whether a deviation has occurred is determined based on the lateral offset distance.

[0046] S103. If the target vehicle deviates, the yaw warning factor of the target vehicle shall be determined based on the target vehicle’s speed, relative distance and lateral deviation distance. The relative distance is the distance from the target vehicle to the starting point of the approach lane.

[0047] In some embodiments, the yaw warning factor of the target vehicle is determined based on the target vehicle's speed, relative distance, and lateral offset distance, including: determining the target vehicle's safety barrier distance based on the speed; subtracting the relative distance from the safety barrier distance to obtain a first distance difference; taking the maximum value between the first distance difference and 0 as the remaining safe distance between the target vehicle and the approach lane; adding half the lane width of the approach lane to the remaining safe distance to obtain a reference distance; and determining the ratio of the lateral offset distance to the reference distance as the yaw warning factor.

[0048] For example, if the target vehicle deviates, i.e., the field is_deviation=true corresponding to whether deviation has occurred, is determined based on the distance (i.e., relative distance) from the target vehicle to the starting point of the approach lane. Lateral offset distance driving speed The specific steps to determine the yaw warning factor for the target vehicle are as follows:

[0049] Based on driving speed Calculate the distance to the safety barrier Specifically, it satisfies the following formula:

[0050]

[0051] in, For empirical braking acceleration, For a fixed buffer distance.

[0052] Accordingly, the remaining safe distance and yaw warning factor They respectively satisfy the following formulas:

[0053]

[0054]

[0055] in, Lane width, which can be taken as an empirical value such as 3.5 meters, yaw warning factor. Lateral deviation distance Proportional to the remaining safe distance Inversely proportional.

[0056] S104. If the yaw warning factor is greater than the preset yaw warning trigger threshold, trigger a yaw warning for the target vehicle.

[0057] For example, assuming the yaw warning trigger threshold is f_threshold, if the yaw warning factor If the value is greater than f_threshold, a yaw warning is triggered for the target vehicle. The yaw warning may include, but is not limited to, at least one of the following: audible warning, vibration warning, and light warning.

[0058] It should be noted that the yaw warning trigger threshold can be flexibly adjusted by combining at least one of the following: vehicle dynamic characteristics, environmental risks, driver characteristics, or historical yaw warning trigger thresholds. Vehicle dynamic characteristics include, but are not limited to, vehicle speed or vehicle type; environmental risks include, but are not limited to, road geometry, road type, weather and lighting conditions, or traffic density; and driver characteristics include, but are not limited to, driver skill level or user preference settings.

[0059] The intersection deviation warning method provided in this application obtains lane information of the entrance lane of the first navigation intersection ahead based on the target vehicle's navigation path in advance, achieving refined monitoring of the vehicle's driving status. It can not only accurately determine whether the vehicle has deviated, and the direction and lateral deviation distance, but also obtain deviation warning factors by comprehensively quantifying driving speed, relative distance, and lateral deviation distance. Furthermore, it determines whether to trigger a deviation warning based on the deviation warning factors. This multi-dimensional parameter fusion warning mechanism significantly improves the predictive ability of deviation risk, and can trigger warnings in time before the vehicle actually deviates. It effectively solves the problem of the lag in traditional navigation systems that can only provide reminders after the fact, thus significantly enhancing the early warning capability of intersection deviation. In turn, it effectively reduces the deviation risk caused by lane selection errors, which is of great significance for improving intersection traffic efficiency, reducing traffic congestion and accident rates, and providing drivers with more forward-looking safety protection.

[0060] In some embodiments, the yaw warning includes deviation from bearing, lateral offset distance, and relative distance. When the yaw warning factor is greater than a preset yaw warning trigger threshold, a yaw warning is triggered for the target vehicle, including: determining the threshold difference between the yaw warning factor and the yaw warning trigger threshold; and triggering a yaw warning of the corresponding level based on the interval range to which the threshold difference belongs.

[0061] For example, in If it is greater than f_threshold, determine The difference Δf between f and f_threshold. Correspondingly, when 0.05 < Δf ≤ 0.1, a general yaw warning is triggered, such as a voice announcement of deviation from bearing, lateral deviation distance, and relative distance, and simultaneously a single beep at a frequency of, for example, 2000 Hz and a duration of, for example, 0.5 s, a yellow warning icon displayed on the instrument panel at a frequency of, for example, 1 Hz, or a slight vibration of the steering wheel for, for example, 1 s. When Δf > 0.1, an emergency yaw warning is triggered, such as a voice announcement of deviation from bearing, lateral deviation distance, and relative distance, and simultaneously a continuous beep at a frequency of 2500 Hz and a time interval of 0.3 s, a dynamic display of the deviation direction in a red warning box on the head-up display (HUD), seat vibration (the intensity increases with the Δf value), or automatic tightening of the seat belt, etc.

[0062] It should be noted that the above The range of the interval corresponding to the difference Δf between f and f_threshold is only an example. In actual applications, it can be flexibly divided according to application requirements, and no limitation is made here.

[0063] In this embodiment, by mapping the difference between the yaw warning factor and the yaw warning trigger threshold to a preset range and associating different warning levels, a refined graded warning for deviation risk is achieved. Based on the dynamic judgment of the threshold difference, the corresponding warning intensity can be matched, which reduces excessive warning interference in low-risk scenarios and ensures that a sufficiently strong warning is provided in high-risk situations, thereby improving driving safety while optimizing the driving experience.

[0064] In some embodiments, before determining the deviation state of the target vehicle based on lane information, the method further includes: determining the relative distance between the target vehicle and the starting point of the approach lane based on lane information; if the relative distance is less than the yaw check distance threshold, then determining the deviation state of the target vehicle based on lane information.

[0065] For example, the coordinates of the starting point of the approach lane are obtained, which could be, for example, the starting point of the lane centerline; accordingly, based on the position coordinates of the target vehicle and the starting coordinates of the lane centerline, the relative distance from the target vehicle to the starting point of the approach lane is determined. ;Will Compare with the preset yaw check distance threshold d_check; if If the relative distance is less than d_check (assuming d_check is 200 meters), then when the relative distance is less than 200 meters, deviation detection will begin, and the steps to determine the deviation status of the target vehicle based on lane information will be executed; if the relative distance is greater than or equal to 200 meters, then deviation detection will not be performed.

[0066] It should be noted that the yaw check distance threshold of 200 meters is just an example. In actual applications, it can be flexibly adjusted according to actual needs or application scenarios, and no limitation is made here.

[0067] In this embodiment, by setting a yaw verification distance threshold, deviation detection is only initiated when the target vehicle enters a critical area (near an intersection), reducing the waste of resources from continuous calculations and significantly reducing the computational load. At the same time, it can effectively eliminate invalid detections in long-distance scenarios, such as when the vehicle has not yet entered the lane change guidance zone, preventing premature false alarms caused by road curvature or positioning errors, and improving the accuracy of early warnings.

[0068] In some embodiments, determining the target boundary lane in the first navigation intersection ahead that is in the same direction as the approach lane based on lane information includes: starting with the approach lane as the starting lane, recursively searching for lanes in the first navigation intersection ahead that have the same lane turning type as the approach lane along the target direction until the lane turning type is different from the lane turning type of the approach lane, and then stopping the recursive search, and determining the last lane with the same lane turning type as the approach lane as the target boundary lane.

[0069] For example, suppose the intersections at the first navigation intersection ahead, from left to right, are: Left Turn A, Left Turn B, Straight, and Right Turn, and the planned navigation path is a left turn. Correspondingly, if Left Turn A is selected as the entry lane (cross_enter_lane), when searching for the left boundary lane, it starts with Left Turn A and recursively searches for lanes with the same turning type as the entry lane at the first navigation intersection in the left direction. However, since there is no lane to the left of Left Turn A, Left Turn A is determined to be the left boundary lane. Similarly, when searching for the right boundary lane, it recursively searches from Left Turn A to the right. Since Left Turn B has the same turning type as Left Turn A, the recursive search continues. When recursively searching for the straight lane, since Left Turn A has a different turning type than the straight lane, the recursive search stops, and Left Turn B is determined to be the right boundary lane.

[0070] In this embodiment, by sequentially searching adjacent lanes of the same steering type from the entrance lane along the target direction, the boundary lane matching the current driving intention in the complex intersection topology can be accurately identified, significantly improving lane matching accuracy compared to the fixed distance search method. Using steering type consistency as the recursion termination condition can effectively eliminate interference from adjacent lanes of opposite direction, ensuring that the finally determined target boundary lane maintains directional consistency with the actual driving path of the vehicle. This recursive mechanism can adapt to intersection scenarios with multiple lanes extending in parallel (such as continuous left-turn lanes) and accurately handle lane changes or forks, providing a precise geometric reference benchmark for subsequent deviation detection, thereby comprehensively improving the consistency between the navigation path and the actual lane position.

[0071] In one possible implementation, determining the deviation state of the target vehicle based on its position coordinates and lane information of the target boundary lane includes: acquiring two reference coordinate points on the centerline of the target boundary lane; determining the deviation direction of the target vehicle based on the vector relationship formed by the position coordinates of the target vehicle and the two reference coordinate points; determining the lateral distance between the target vehicle and the centerline of the target boundary lane using operations between the position coordinates and the vector formed by the two reference coordinate points; subtracting half the lane width of the target boundary lane from the lateral distance to obtain a second distance difference; taking the maximum value between the second distance difference and 0 as the lateral offset distance; and determining whether the target vehicle has deviated based on the sign of the lateral offset distance.

[0072] For example, initialize the deviation status of the target vehicle, such as whether deviation has occurred (is_deviation=false), deviation direction (deviation_dir=""), and deviation distance. Locate the left-bound lane; determine the target vehicle's deviation from the left-bound lane and its lateral offset distance. Specifically, determine the target vehicle's relative position to the lane centerline of the left-bound lane. .

[0073] Accordingly, if If the value is "left", then calculate the lateral offset distance of the target vehicle from the left boundary lane. For example, first calculate the lateral distance d_left_bound_lane of the target vehicle relative to the left boundary lane. This can be done by using the point-to-line distance method to obtain the lateral offset distance of the target vehicle relative to the left boundary lane. , Satisfy the following formula:

[0074]

[0075] like , then is_deviation=true, deviation_dir="left", ;like If the target vehicle has not deviated, it indicates that the target vehicle has not deviated and returns is_deviation=false, deviation_dir="", and deviation distance. .

[0076] Correspondingly, if If the value is "right", then locate the right boundary lane (right_bound_lane); determine the target vehicle's deviation direction and lateral offset distance relative to the right boundary lane (right_bound_lane), specifically, determine the target vehicle's relative position to the lane centerline of the right boundary lane. ;like If the value is "right", then calculate the lateral offset distance of the target vehicle from the right boundary lane. For example, first calculate the lateral distance d_right_bound_lane of the target vehicle relative to the right boundary lane. Specifically, this can be calculated using the point-to-line distance method to obtain the lateral offset distance of the target vehicle relative to the right boundary lane. , Satisfy the following formula:

[0077]

[0078] like , then is_deviation=true, deviation_dir="right", ;like If the target vehicle has not deviated, it indicates that the target vehicle has not deviated and returns is_deviation=false, deviation_dir="", and deviation distance. .

[0079] The deviation of the target vehicle from the target boundary lane is determined in the following way:

[0080] For example, suppose The coordinates of the center point of the target vehicle. , For example, two points are arbitrarily selected from the center line of the lane of the target boundary lane. , The starting and ending points of the lane centerline can be taken separately. Among these, the calculation of known points... with by , The formula for determining the left and right directions of a line defined by a point is as follows:

[0081]

[0082] like If the deviation is "left", then the deviation is considered "left"; if If the deviation is "right", then the deviation is "right"; otherwise, it indicates that no deviation has occurred and the center point of the target vehicle is on the center line of the target boundary lane.

[0083] In addition, the lateral distance between the target vehicle and the target boundary lane satisfies the following formula:

[0084]

[0085] in, This refers to the lateral distance of the target vehicle relative to the target boundary lane, such as the lateral distance d_left_bound_lane of the target vehicle relative to the left boundary lane, or the lateral distance d_right_bound_lane of the target vehicle relative to the right boundary lane.

[0086] For example, Figure 2 A schematic diagram of the deviation state provided for an exemplary embodiment of this application. For example... Figure 2As shown in the figure, assume that the target lane of the first navigation intersection ahead is the straight lane. If Lane3 is selected as the import lane of the target vehicle, the left boundary lane is Lane2 and the right boundary lane is Lane4. Correspondingly, the target vehicle is analyzed when it is at points P1, P2, P3, P4, and P5 respectively. Specifically, when the target vehicle is at point P1, the target vehicle is on the left side of the center line of the left boundary lane Lane2, that is, dir_left is "left", d_left_bound_lane and d_lat_left are as shown in the figure, and d_lat_left > 0. At this time, the deviation state of the target vehicle is a left deviation, and the deviation distance is d_lat_left; when the target vehicle is at point P2, the target vehicle is on the left side of the center line of the left boundary lane Lane2, that is, dir_left is "left", d_left_bound_lane is as shown in the figure. Since d_left_bound_lane < lane_width / 2, d_lat_left = 0, and there is no deviation of the target vehicle at this time; when the target vehicle is at points P3 and P4, the target vehicle is on the right side of the center line of the left boundary lane Lane2 and on the left side of the center line of the right boundary lane Lane4. At this time, the target vehicle has no deviation; when the target vehicle is at point P5, the target vehicle is on the right side of the center line of the right boundary lane Lane4, that is, dir_left is "right", d_right_bound_lane and d_lat_right are as shown in the figure, and d_lat_right > 0. At this time, the deviation state of the target vehicle is a right deviation, and the deviation distance is d_lat_right.

[0087] In the embodiment of the present application, by obtaining the vector relationship between two reference points of the lane center line and the vehicle position, the lateral offset distance and deviation direction of the vehicle relative to the lane center line can be accurately calculated, significantly improving the detection accuracy in complex curved road scenarios; in addition, by adopting the lane half-width threshold comparison mechanism and introducing zero-value truncation processing, the small offset false alarms caused by lane line recognition errors or positioning jitters can be effectively filtered; at the same time, by directly associating the actual vehicle position with the lane geometric features through vector operations, it is not only applicable to straight lanes, but also can accurately adapt to the deviation detection of curved lanes, greatly improving the robustness and reliability in various road scenarios.

[0088] Figure 3 This is another flowchart of the intersection yaw warning method provided by the exemplary embodiment of the present application. As Figure 3 shown, the intersection yaw warning method includes the following steps:

[0089] S301. Based on the navigation path of the target vehicle, obtain the lane information of the import lane of the first navigation intersection ahead.

[0090] S302. Based on lane information, determine the relative distance from the target vehicle to the starting point of the entrance lane.

[0091] S303. Determine whether the relative distance is less than the yaw check distance threshold.

[0092] If not, proceed to S302;

[0093] If so, execute S304.

[0094] S304. Based on lane information, determine the left boundary lane that is in the same direction as the approach lane at the first navigation intersection ahead.

[0095] S305. Determine the deviation of the target vehicle from the left boundary lane.

[0096] S306. Determine whether the deviation is to the left.

[0097] If so, execute S307;

[0098] If not, proceed with S310.

[0099] S307. Determine the left lateral offset distance of the target vehicle relative to the lane centerline of the left boundary lane.

[0100] The left lateral offset distance is the lateral offset distance of the target vehicle relative to the left boundary lane. .

[0101] S308. Determine if the left lateral offset distance is greater than 0.

[0102] If so, execute S309;

[0103] If not, proceed to S316.

[0104] S309. Determine that a deviation has occurred, the deviation direction is to the left and the left lateral offset distance is the lateral offset distance.

[0105] S310: Based on lane information, determine the right boundary lane that is in the same direction as the approach lane at the first navigation intersection ahead.

[0106] S311. Determine the deviation of the target vehicle from the right boundary lane.

[0107] S312. Determine whether the deviation is to the right.

[0108] If so, execute S313;

[0109] If not, proceed to S16.

[0110] S313. Determine the right lateral offset distance of the target vehicle relative to the lane centerline of the right boundary lane.

[0111] The right lateral offset distance refers to the lateral offset distance of the target vehicle relative to the right boundary lane. .

[0112] S314. Determine if the right lateral offset distance is greater than 0.

[0113] If so, execute S315;

[0114] If not, proceed to S316.

[0115] S315. Determine that a deviation has occurred, the deviation direction is to the right and the right lateral offset distance is the lateral offset distance.

[0116] S316. Confirm that no deviation has occurred.

[0117] It should be noted that the above example of first executing S304 to determine the left boundary lane in the same direction as the approach lane is only one example. Alternatively, S310 can be executed first to determine the right boundary lane in the same direction as the approach lane. In actual application, the execution order of S304 and S310 is not limited.

[0118] In summary, this application has at least the following advantages:

[0119] I. By obtaining lane information of the first approach lane at the navigation intersection ahead based on the target vehicle's navigation path, refined monitoring of vehicle driving status is achieved. This not only accurately determines whether the vehicle has deviated, and the direction and lateral deviation distance, but also obtains a yaw warning factor by comprehensively quantifying driving speed, relative distance, and lateral deviation distance. Further, based on the yaw warning factor, it determines whether to trigger a yaw warning. This multi-dimensional parameter fusion warning mechanism significantly improves the predictive ability of yaw risk, triggering warnings in time before the vehicle actually deviates. This effectively solves the problem of the lag in traditional navigation systems, which can only provide after-the-fact reminders. Therefore, it significantly enhances the early warning capability for intersection yaw, thereby effectively reducing the risk of yaw due to lane selection errors. This is of great significance for improving intersection traffic efficiency, reducing traffic congestion and accident rates, and providing drivers with more proactive safety guarantees.

[0120] Second, by mapping the difference between the yaw warning factor and the yaw warning trigger threshold to a preset range and associating different warning levels, a refined graded warning for deviation risk is achieved; based on the dynamic judgment of the threshold difference, the corresponding warning intensity can be matched, which reduces excessive warning interference in low-risk scenarios and ensures that a sufficiently strong warning is provided in high-risk situations, thereby improving driving safety while optimizing the driving experience.

[0121] Third, by starting from the entrance lane and sequentially searching adjacent lanes of the same turning type along the target direction, it can accurately identify the boundary lanes in complex intersection topologies that match the current driving intention, significantly improving lane matching accuracy compared to the fixed-distance search method. Using the consistency of turning type as the recursion termination condition can effectively eliminate the interference of adjacent lanes with opposite directions, ensuring that the finally determined target boundary lane maintains directional consistency with the actual driving path of the vehicle. This recursive mechanism can adapt to intersection scenarios with multiple lanes extending in parallel (such as continuous left-turn lanes) and accurately handle lane changes or forks, providing a precise geometric reference benchmark for subsequent deviation detection, thereby comprehensively improving the consistency between the navigation path and the actual lane position.

[0122] Fourth, by obtaining the vector relationship between the two reference points of the lane centerline and the vehicle position, the lateral offset distance and deviation direction of the vehicle relative to the lane centerline can be accurately calculated, significantly improving the detection accuracy in complex curved scenarios. In addition, by adopting a lane half-width threshold comparison mechanism and introducing zero-value truncation processing, it can effectively filter out minor offset false alarms caused by lane line recognition errors or positioning jitter. At the same time, by directly associating the actual position of the vehicle with the lane geometric features through vector operations, it is not only applicable to straight lanes, but can also accurately adapt to deviation detection in curved lanes, greatly improving robustness and reliability in various road scenarios.

[0123] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0124] Figure 4 A schematic diagram of a road yaw warning device provided as an exemplary embodiment of this application. Figure 4 As shown, the yaw warning device 40 at the intersection includes an acquisition module 41, a first determination module 42, a second determination module 43, and a yaw warning module 44, wherein:

[0125] The acquisition module 41 is used to acquire lane information of the entrance lane of the first navigation intersection ahead based on the navigation path of the target vehicle.

[0126] The first determining module 42 is used to determine the deviation status of the target vehicle based on lane information. The deviation status includes whether a deviation has occurred, as well as the deviation direction and lateral offset distance when a deviation occurs.

[0127] The second determining module 43 is used to determine the yaw warning factor of the target vehicle based on the target vehicle's driving speed, relative distance and lateral offset distance when the target vehicle deviates. The relative distance is the distance from the target vehicle to the starting point of the approach lane.

[0128] Yaw warning module 44 is used to trigger a yaw warning for the target vehicle when the yaw warning factor is greater than the preset yaw warning trigger threshold.

[0129] In one possible implementation, the first determining module 42 may be specifically used to: determine the relative distance between the target vehicle and the starting point of the entrance lane based on lane information; if the relative distance is less than the yaw verification distance threshold, then determine the deviation state of the target vehicle based on lane information.

[0130] In one possible implementation, the second determining module 43 may be specifically used to: determine the safety barrier distance of the target vehicle based on the driving speed; subtract the relative distance from the safety barrier distance to obtain a first distance difference; take the maximum value between the first distance difference and 0 as the remaining safe distance between the target vehicle and the approach lane; add half the lane width of the approach lane to the remaining safe distance to obtain a reference distance; and determine the ratio of the lateral offset distance to the reference distance as the yaw warning factor.

[0131] In one possible implementation, the first determining module 42 can also be used to: determine the target boundary lane in the same direction as the approach lane at the first navigation intersection ahead based on lane information; and determine the deviation state of the target vehicle based on the position coordinates of the target vehicle and the lane information of the target boundary lane.

[0132] In one possible implementation, the first determining module 42 can also be used to: take the inbound lane as the starting lane, recursively search for lanes with the same lane turning type as the inbound lane at the first navigation intersection ahead along the target direction, until the recursive search stops when the lane turning type is different from the lane turning type of the inbound lane, and determine the last lane with the same lane turning type as the inbound lane as the target boundary lane.

[0133] In one possible implementation, the first determining module 42 can also be used to: acquire two reference coordinate points on the center line of the target boundary lane; determine the deviation direction of the target vehicle based on the vector relationship formed by the position coordinates of the target vehicle and the two reference coordinate points; determine the lateral distance between the target vehicle and the center line of the target boundary lane by using the operation between the position coordinates and the vector formed by the two reference coordinate points; subtract half of the lane width of the target boundary lane from the lateral distance to obtain a second distance difference; take the maximum value between the second distance difference and 0 as the lateral offset distance; and determine whether the target vehicle has deviated based on the sign of the lateral offset distance.

[0134] In one possible implementation, the yaw warning includes deviation from bearing, lateral offset distance, and relative distance. The yaw warning module 44 can be specifically used to: determine the threshold difference between the yaw warning factor and the yaw warning trigger threshold; and trigger a yaw warning of the corresponding level based on the range to which the threshold difference belongs.

[0135] The intersection velocity warning device provided in this application embodiment can execute the technical solution shown in the above-described intersection velocity warning method embodiment. Its implementation principle and beneficial effects are similar, and will not be described again here.

[0136] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0137] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0138] It should be noted that the above-described device embodiments are merely illustrative, and the device of this application can also be implemented in other ways; and it should be understood that the division of the various modules of the above device is only a logical functional division, and in actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, these modules can all be implemented in software through processing element calls; they can all be implemented in hardware; or some modules can be implemented by processing element calls to software, and some modules can be implemented in hardware. For example, the yaw warning module can be a separately established processing element, or it can be integrated into a chip of the above device. Alternatively, it can be stored as program code in the memory of the above device, and its function can be called and executed by a processing element of the above device. The implementation of other modules is similar. In addition, these modules can be fully or partially integrated together, or they can be implemented independently. The processing element here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each of the above modules can be completed by the integrated logic circuit in the hardware of the processor element or by software instructions.

[0139] For example, these modules can be one or more integrated circuits configured to implement the above methods, such as one or more Application Specific Integrated Circuits (ASICs), one or more Digital Signal Processors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs). As another example, when a module is implemented using processing element scheduler code, the processing element can be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. Furthermore, these modules can be integrated together as a System-On-a-Chip (SOC).

[0140] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., Digital Video Discs, DVDs), or semiconductor media (e.g., solid-state disks (SSDs)).

[0141] Figure 5 A schematic diagram of the structure of an electronic device provided as an exemplary embodiment of this application. For example... Figure 5 As shown, the electronic device 50 in this embodiment includes:

[0142] At least one processor 51; and a memory 52 communicatively connected to said at least one processor;

[0143] The memory 52 stores instructions that can be executed by the at least one processor 51 to cause the electronic device to perform the method as described in any of the above embodiments.

[0144] Alternatively, the memory 52 can be either standalone or integrated with the processor 51.

[0145] The memory 52 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device.

[0146] The processor 51 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. Specifically, when implementing the intersection descent warning method described in the foregoing method embodiments, the electronic device may be, for example, an electronic device with processing capabilities such as a server.

[0147] Optionally, the electronic device may also include a communication interface 53. In specific implementations, if the communication interface 53, memory 52, and processor 51 are implemented independently, they can be interconnected via a bus to complete communication. 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., but this does not imply that there is only one bus or one type of bus.

[0148] Optionally, in a specific implementation, if the communication interface 53, memory 52 and processor 51 are integrated on a single chip, then the communication interface 53, memory 52 and processor 51 can communicate through an internal interface.

[0149] The implementation principle and technical effects of the electronic device provided in this embodiment can be found in the foregoing embodiments, and will not be repeated here.

[0150] This application also provides a computer-readable storage medium storing computer-executable instructions. When the computer-executable instructions are executed, they are used to implement the method steps as described in the above method embodiments. The specific implementation methods and technical effects are similar, and will not be repeated here.

[0151] The aforementioned computer-readable storage media can be implemented from any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Read Only Memory (PROM), Read Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0152] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an application-specific integrated circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in a road yaw warning device.

[0153] This application also provides a computer program product, including a computer program, which, when executed, implements the method steps as described in the above method embodiments. The specific implementation and technical effects are similar and will not be repeated here.

[0154] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0155] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0156] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for early warning of deviation at intersections, characterized in that, include: Based on the navigation path of the target vehicle, obtain the lane information of the entrance lane of the first navigation intersection ahead; Based on the lane information, the deviation status of the target vehicle is determined, including whether a deviation has occurred, and the deviation direction and lateral offset distance when a deviation occurs; If the target vehicle deviates, a yaw warning factor for the target vehicle is determined based on the target vehicle's speed, relative distance, and lateral deviation distance, where the relative distance is the distance from the target vehicle to the starting point of the approach lane. If the yaw warning factor is greater than the preset yaw warning trigger threshold, a yaw warning is triggered for the target vehicle. The determination of the yaw warning factor for the target vehicle based on its speed, relative distance, and lateral offset distance includes: Based on the driving speed, determine the safety barrier distance of the target vehicle; Subtracting the relative distance from the safety barrier distance yields the first distance difference. The maximum value between the first distance difference and 0 is taken as the remaining safe distance between the target vehicle and the entrance lane; The baseline distance is obtained by adding half the lane width of the imported lane to the remaining safety distance; The ratio of the lateral offset distance to the reference distance is determined as the yaw warning factor.

2. The intersection deviation early warning method according to claim 1, characterized in that, Before determining the deviation status of the target vehicle based on the lane information, the method further includes: Based on the lane information, determine the relative distance from the target vehicle to the starting point of the entrance lane; If the relative distance is less than the yaw check distance threshold, the deviation state of the target vehicle is determined based on the lane information.

3. The intersection deviation early warning method according to claim 1 or 2, characterized in that, Determining the deviation status of the target vehicle based on the lane information includes: Based on the lane information, determine the target boundary lane that is in the same direction as the entrance lane at the first navigation intersection ahead; Based on the position coordinates of the target vehicle and the lane information of the target boundary lane, the deviation state of the target vehicle is determined.

4. The intersection deviation early warning method according to claim 3, characterized in that, The step of determining the target boundary lane in the same direction as the approach lane at the first navigation intersection ahead, based on the lane information, includes: Starting with the inbound lane, recursively search for lanes with the same lane turning type as the inbound lane at the first navigation intersection ahead in the target direction until the lane turning type is different from that of the inbound lane. The recursive search stops when the last lane with the same lane turning type as the inbound lane is determined as the target boundary lane.

5. The intersection deviation early warning method according to claim 3, characterized in that, Determining the deviation state of the target vehicle based on its position coordinates and lane information of the target boundary lane includes: Obtain two reference coordinate points on the center line of the lane of the target boundary lane; Based on the vector relationship between the target vehicle's position coordinates and the two reference coordinate points, the deviation of the target vehicle is determined; The lateral distance between the target vehicle and the lane centerline of the target boundary lane is determined by using the position coordinates and the vector formed by the two reference coordinate points. Subtract half the lane width of the target boundary lane from the lateral distance to obtain the second distance difference; Take the maximum value between the second distance difference and 0 as the lateral offset distance; Based on the sign of the lateral offset distance, it is determined whether the target vehicle has deviated.

6. The intersection deviation early warning method according to claim 1 or 2, characterized in that, The yaw warning includes the deviation from bearing, the lateral offset distance, and the relative distance. When the yaw warning factor is greater than a preset yaw warning trigger threshold, a yaw warning is triggered for the target vehicle, including: Determine the threshold difference between the yaw warning factor and the yaw warning trigger threshold; Based on the range of the threshold difference, a yaw warning of the corresponding level is triggered.

7. A road descent warning device, characterized in that, include: The acquisition module is used to obtain lane information of the entrance lane of the first navigation intersection ahead, based on the navigation path of the target vehicle. The first determining module is used to determine the deviation state of the target vehicle based on the lane information. The deviation state includes whether a deviation has occurred, and the deviation direction and lateral offset distance when a deviation occurs. The second determining module is used to determine a yaw warning factor for the target vehicle based on its speed, relative distance, and lateral deviation distance when the target vehicle deviates from its lane. The relative distance is the distance from the target vehicle to the starting point of the approach lane. Specifically, the second determining module is used to: determine the safety barrier distance of the target vehicle based on its speed; subtract the relative distance from the safety barrier distance to obtain a first distance difference; take the maximum value between the first distance difference and 0 as the remaining safe distance between the target vehicle and the approach lane; add half the lane width of the approach lane to the remaining safe distance to obtain a reference distance; and determine the ratio of the lateral deviation distance to the reference distance as the yaw warning factor. The yaw warning module is used to trigger a yaw warning for the target vehicle when the yaw warning factor is greater than a preset yaw warning trigger threshold.

8. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory is used to store computer-executed instructions; The processor is configured to execute the computer execution instructions to implement the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed, are used to implement the method as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed, it implements the method as described in any one of claims 1 to 6.

Images