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

Abstract

The invention provides an intersection yaw early warning method, device and equipment, a storage medium and a program product, and relates to the technical field of vehicle driving. The method comprises the following steps: acquiring lane information of an entrance lane of a first navigation intersection in front based on a navigation path of a target vehicle; determining a deviation state of the target vehicle based on the lane information; if the target vehicle deviates, determining a yaw early warning factor based on the driving speed, the relative distance and the lateral deviation distance of the target vehicle; and when the yaw early warning factor is larger than a yaw early warning triggering threshold value, yaw early warning is triggered. According to the method, the lane information of the front entrance lane is acquired in advance, the vehicle driving state is finely monitored, the deviation state of the vehicle can be accurately judged, the yaw early warning factor is obtained by comprehensively quantifying the multi-source information, and whether yaw early warning is triggered or not is judged based on the yaw early warning factor, so that the accuracy of yaw early warning is improved. Early warning can be triggered in time before the vehicle actually yaws, and therefore the early warning capacity of intersection yawing in advance is remarkably enhanced.

Description

Technical Field

[0001] The present application relates to the field of vehicle driving technology, and in particular to a method, device, equipment, storage medium and program product for warning of a course deviation at an intersection. Background Art

[0002] In recent years, with the increasing complexity of road networks and the increasing number of vehicles, the challenges faced by route navigation have become increasingly severe. Especially when navigating into intersections, vehicles often deviate from the correct lane due to choosing 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 usually output a deviation reminder after a vehicle deviates from its course when entering an intersection, but lack the ability to provide early warning of intersection deviation. Summary of the Invention

[0004] The present application provides a method, device, equipment, storage medium and program product for warning of intersection deviation, which are used to enhance the early warning capability of intersection deviation.

[0005] In a first aspect, the present application provides a method for warning of a course deviation at an intersection, comprising:

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

[0007] Determine the target vehicle's deviation state based on lane information, including whether a deviation has occurred, as well as the deviation direction and lateral deviation distance when the 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 offset distance. The relative distance is the distance from the target vehicle to the starting point of the import lane.

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

[0010] In one possible implementation, before determining the deviation state of the target vehicle based on the lane information, the method further includes: determining the relative distance from the target vehicle to the starting point of the import lane based on the lane information; if the relative distance is less than a yaw verification distance threshold, determining the deviation state of the target vehicle based on the lane information.

[0011] In one possible implementation, a yaw warning factor of the target vehicle is determined based on the target vehicle's driving speed, relative distance, and lateral offset distance, including: determining a safety barrier distance of the target vehicle based on the driving 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 safety distance of the target vehicle from the import lane; adding half the lane width of the import lane to the remaining safety 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 a target boundary lane in the same direction as the import lane at the first navigation intersection ahead based on the 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, a target boundary lane in the first navigation intersection ahead that is in the same direction as the import lane is determined, including: taking the import lane as the starting lane, recursively searching along the target direction for a lane in the first navigation intersection ahead that has the same lane turning type as the import lane, stopping the recursive search when the lane turning type is different from the lane turning type of the import lane, and determining the last lane that has the same lane turning type as the import lane as the target boundary lane.

[0014] In one possible implementation, the deviation state of the target vehicle is determined based on the position coordinates of the target vehicle and the lane information of the target boundary lane, including: obtaining two reference coordinate points on the lane 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 lane centerline of the target boundary lane by using operations between the position coordinates and the vectors formed by the two reference coordinate points; subtracting the lateral distance from half the lane width of the target boundary lane 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 positive or negative condition of the lateral offset distance.

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

[0016] In a second aspect, the present application provides a road intersection deviation warning device, comprising:

[0017] An acquisition module, for acquiring lane information of an import lane of a first navigation intersection ahead based on a navigation path of a target vehicle;

[0018] A first determination module is configured to determine a deviation state of the target vehicle based on lane information, where the deviation state includes whether a deviation occurs, and a deviation direction and a lateral deviation distance when the deviation occurs;

[0019] A second determination module is configured to determine a yaw warning factor of the target vehicle based on the target vehicle's speed, relative distance, and lateral offset distance when the target vehicle deviates, where the relative distance is the distance from the target vehicle to the starting point of the import 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 a preset yaw warning trigger threshold.

[0021] In a third aspect, the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0022] Memory for storing computer-executable instructions;

[0023] A processor is configured to execute computer-executable instructions stored in a memory to implement the method described in any one of the first aspects.

[0024] In a fourth aspect, the present application provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are executed, they are used to implement any of the methods described in the first aspect.

[0025] In a fifth aspect, the present application provides a computer program product, comprising a computer program, which implements the method described in any one of the first aspects when executed.

[0026] The intersection deviation warning method, device, equipment, storage medium and program product provided by the present application obtain the lane information of the import 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, the deviation status including whether deviation occurs, and the deviation direction and lateral offset distance when the deviation occurs; if the target vehicle deviates, the yaw warning factor of the target vehicle 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 import lane; further, when the yaw warning factor is greater than a preset yaw warning trigger threshold, a yaw warning is triggered for the target vehicle. During this process, by obtaining lane information of the entrance lane of the first navigation intersection ahead in advance based on the navigation path of the target vehicle, refined monitoring of the vehicle's driving status is achieved. This not only accurately determines whether the vehicle has deviated, as well as the deviation direction and lateral offset distance, but also obtains a yaw warning factor by comprehensively quantifying the driving speed, relative distance and lateral offset distance. Further, based on the yaw warning factor, it is determined whether to trigger a yaw warning. This warning mechanism with multi-dimensional parameter fusion significantly improves the ability to predict yaw risks and can trigger a warning in time before the vehicle actually deviates. It effectively solves the lag problem of traditional navigation systems that can only provide reminders after the fact, thereby significantly enhancing the early warning capability of intersection yaw, and effectively reducing the yaw risk caused by incorrect lane selection. This is of great significance for improving intersection traffic efficiency, reducing traffic congestion and accident rates, and providing more forward-looking safety protection for drivers. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0028] Figure 1 A schematic diagram of a flow chart of a method for warning of a course deviation at an intersection provided by an exemplary embodiment of the present application;

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

[0030] Figure 3 Another schematic diagram of a flow chart of a method for warning of a course deviation at an intersection provided by an exemplary embodiment of the present application;

[0031] Figure 4 A schematic structural diagram of a road intersection deviation warning device provided by an exemplary embodiment of the present application;

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

[0033] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0034] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0035] The terms "first", "second" etc. in the specification and claims of the present application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable in appropriate circumstances, so that the embodiments of the present application described herein can, for example, be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, the process, system, product or equipment comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or that are inherent to these processes, products or equipment.

[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, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards, and corresponding operation entrances must be provided for users to choose to authorize or refuse.

[0037] In related technologies, traditional navigation systems usually output a deviation warning after the vehicle deviates from the course when entering an intersection, but are unable to predict risks before the deviation occurs. They lack the ability to provide early warning of intersection deviation, resulting in the warning time window lagging behind the optimal adjustment period. This not only affects the driving experience, but may also affect the traffic efficiency of the intersection, leading to traffic congestion and even traffic accidents.

[0038] In order to solve the above problems, an embodiment of the present application provides a deviation warning solution for intersections. By real-time analysis of the navigation path of the target vehicle and loading the lane information of the entrance lane of the first intersection ahead, combined with high-precision positioning, the deviation status of the target vehicle is dynamically determined. When deviation is detected, a yaw warning factor integrating time, space and speed characteristics is constructed by combining multi-source information. Furthermore, when the yaw warning factor exceeds the threshold, a yaw warning is triggered for the target vehicle, realizing active safety intervention from "reminder after deviation" to "prediction before deviation", significantly enhancing the early warning capability of intersection deviation, and thus effectively reducing the risk of yaw caused by incorrect lane selection, 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.

[0039] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0040] Figure 1 A flow chart of a method for warning of a course deviation at an intersection provided by an exemplary embodiment of the present application. Figure 1 As shown, the intersection deviation warning method includes the following steps:

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

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

[0043] S102: Determine the deviation state of the target vehicle based on the lane information, where the deviation state includes whether deviation occurs, and the deviation direction and lateral deviation distance when the deviation occurs.

[0044] In some embodiments, the deviation state of the target vehicle is determined based on lane information, including: determining the target boundary lane in the same direction as the import lane in the first navigation intersection ahead based on the lane information; 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 lane centerline of the target boundary lane, such as the deviation direction being "left" or the deviation direction being "right"; the lateral offset distance is determined based on the vertical distance from the target vehicle to the lane centerline of the target boundary lane; and whether deviation occurs is determined based on the lateral offset distance.

[0046] S103. If the target vehicle deviates, a yaw warning factor of the target vehicle is determined based on the target vehicle's speed, relative distance, and lateral offset distance. The relative distance is the distance from the target vehicle to the starting point of the import lane.

[0047] In some embodiments, a yaw warning factor of a target vehicle is determined based on the target vehicle's driving speed, relative distance, and lateral offset distance, including: determining a safety barrier distance of the target vehicle based on the driving 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 safety distance of the target vehicle from the import lane; adding half the lane width of the import lane to the remaining safety 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, that is, the corresponding field is_deviation=true, based on the distance from the target vehicle to the starting point of the import lane (i.e., relative distance) , lateral offset distance , driving speed , determine the yaw warning factor of the target vehicle. The specific steps are as follows:

[0049] According to driving speed Calculating safety barrier distance , specifically satisfying the following formula:

[0050]

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

[0052] Accordingly, the remaining safety distance and yaw warning factor Satisfy the following formulas respectively:

[0053]

[0054]

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

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

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

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

[0059] The intersection deviation warning method provided in the embodiment of the present application realizes refined monitoring of the vehicle's driving status by obtaining lane information of the entrance lane of the first navigation intersection ahead in advance based on the navigation path of the target vehicle. It can not only accurately determine whether the vehicle has deviated, the deviation direction and lateral offset distance, but also obtain a yaw warning factor by comprehensively quantifying the driving speed, relative distance and lateral offset distance. It further determines whether to trigger the yaw warning based on the yaw warning factor. This warning mechanism with multi-dimensional parameter fusion significantly improves the prediction ability of yaw risk and can trigger a warning in time before the vehicle actually deviates. It effectively solves the lag problem of traditional navigation systems that can only remind after the fact, thereby significantly enhancing the early warning ability of intersection deviation, and effectively reducing the yaw risk caused by incorrect lane selection. It is of great significance for improving intersection traffic efficiency, reducing traffic congestion and accident rates, and providing more forward-looking safety protection for drivers.

[0060] In some embodiments, the yaw warning includes deviation direction, lateral offset distance and relative distance. When the yaw warning factor is greater than a preset yaw warning trigger threshold, a yaw warning for the target vehicle is triggered, including: determining the threshold difference between the yaw warning factor and the yaw warning trigger threshold; and triggering a yaw warning of a level corresponding to the interval range according to 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 the threshold and f_threshold. Correspondingly, when 0.05<Δf≤0.1, the trigger level is a general yaw warning, such as a voice announcement of the deviation direction, lateral deviation distance, and relative distance, and a single beep with a frequency of, for example, 2000 Hz and a duration of, for example, 0.5 seconds, 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 lasting, for example, 1 second. When Δf>0.1, the trigger level is an emergency yaw warning, such as a voice announcement of the deviation direction, lateral deviation distance, and relative distance, and a continuous beep with a frequency of 2500 Hz and a time interval of 0.3 seconds, a red warning box on the Head-Up Display (HUD) dynamically displaying the deviation direction, seat vibration (increasing in intensity with increasing Δf), or automatic seat belt tightening.

[0062] It should be noted that the above The interval range corresponding to the difference Δf from f_threshold is only an example. In actual applications, it can be flexibly divided according to application requirements and is not limited here.

[0063] In the embodiment of the present application, by mapping the difference between the yaw warning factor and the yaw warning trigger threshold to a preset interval range and associating different warning levels, a refined graded warning of deviation risk is achieved; dynamic judgment based on the threshold difference can match the corresponding warning intensity, which not only reduces excessive warning interference in low-risk scenarios, but also ensures that sufficiently strong warnings are 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 from the target vehicle to the starting point of the import lane based on the lane information; if the relative distance is less than the yaw verification distance threshold, determining the deviation state of the target vehicle based on the lane information.

[0065] For example, the coordinates of the starting point of the import lane are obtained, and the starting point can be, for example, the starting point of the lane centerline of the import lane; 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 import lane is determined. ;Will Compare with the preset yaw check distance threshold d_check; if Less than d_check. Assuming d_check is 200 meters, when the relative distance is less than 200 meters, deviation detection is started, and the step of determining the deviation state of the target vehicle based on lane information is executed; if the relative distance is greater than or equal to 200 meters, deviation detection is not performed.

[0066] It should be noted that the yaw calibration distance threshold of 200 meters is only an example. In actual applications, it can be flexibly adjusted according to actual needs or application scenarios and is not limited here.

[0067] In the embodiment of the present application, by setting a deviation verification distance threshold, deviation detection is initiated only when the target vehicle enters a critical area (near an intersection), thereby reducing the waste of resources for uninterrupted calculations throughout the entire process and significantly reducing the computing 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, prevent premature false alarms caused by road curvature or positioning errors, and improve the accuracy of early warnings.

[0068] In some embodiments, based on lane information, a target boundary lane in the first navigation intersection ahead that is in the same direction as the import lane is determined, including: taking the import lane as the starting lane, recursively searching along the target direction for a lane in the first navigation intersection ahead that has the same lane turning type as the import lane, stopping the recursive search when the lane turning type is different from the lane turning type of the import lane, and determining the last lane that has the same lane turning type as the import lane as the target boundary lane.

[0069] For example, assume that the intersections at the first navigation intersection ahead are, from left to right, left turn A, left turn B, straight ahead, and right turn, and that the navigation plan path is a left turn. Accordingly, if left turn A is selected as the entry lane cross_enter_lane, when searching for the left boundary lane, left turn A is used as the starting lane, and a recursive search is performed to the left of the first navigation intersection for a lane with the same lane turning type as the entry lane. However, since there is no lane to the left of left turn A, left turn A is determined to be the left boundary lane. Accordingly, when searching for the right boundary lane, the search is recursively performed from left turn A to the right. Since left turn B has the same lane turning type as left turn A, the recursive search continues. When recursively reaching the straight lane, since left turn A and the straight lane have different lane turning types, the recursive search is stopped, and left turn B is determined to be the right boundary lane.

[0070] In an embodiment of the present application, by starting from the entrance lane and searching for adjacent lanes of the same turning type step by step along the target direction, it is possible to accurately identify the boundary lanes that match the current driving intention in a complex intersection topology, significantly improving the lane matching accuracy compared to the fixed-distance search method; using turning type consistency as the recursive termination condition can effectively eliminate the interference of adjacent opposite-direction lanes, ensuring that the final target boundary lane maintains directional consistency with the actual vehicle driving path; this recursive mechanism can not only adapt to intersection scenarios with multiple lanes extending in parallel (such as continuous left-turn lanes), but also accurately handle lane gradients or bifurcations, 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, the deviation state of the target vehicle is determined based on the position coordinates of the target vehicle and the lane information of the target boundary lane, including: obtaining two reference coordinate points on the lane 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 lane centerline of the target boundary lane by using operations between the position coordinates and the vectors formed by the two reference coordinate points; subtracting the lateral distance from half the lane width of the target boundary lane 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 positive or negative condition of the lateral offset distance.

[0072] For example, initialize the deviation state of the target vehicle, such as whether deviation occurs is_deviation=false, deviation direction deviation_dir="", deviation distance ; Find the left boundary lane left_bound_lane; Determine the deviation direction and lateral offset distance of the target vehicle relative to the left boundary lane left_bound_lane. Specifically, determine the relative direction of the target vehicle to the centerline of the left boundary lane .

[0073] Accordingly, if If it is "left", the lateral offset distance from the target vehicle to the left boundary lane is calculated. For example, the lateral distance d_left_bound_lane of the target vehicle relative to the left boundary lane is calculated first. Specifically, the point-to-straight-line distance can be used to calculate the lateral offset distance of the target vehicle relative to the left boundary lane. , Satisfies the following formula:

[0074]

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

[0076] Correspondingly, if If it is "right", then find the right boundary lane right_bound_lane; determine the deviation direction and lateral offset distance of the target vehicle relative to the right boundary lane right_bound_lane, specifically, determine the relative direction of the target vehicle to the lane centerline of the right boundary lane ;like If it is "right", the lateral offset distance from the target vehicle to the right boundary lane is calculated. For example, the lateral distance d_right_bound_lane of the target vehicle relative to the right boundary lane is calculated first. Specifically, the point-to-straight-line distance can be used to calculate the lateral offset distance of the target vehicle relative to the right boundary lane. , Satisfies the following formula:

[0077]

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

[0079] The deviation direction of the target vehicle relative to the target boundary lane is determined in the following manner:

[0080] For example, suppose is the center point coordinate of the target vehicle, , are two points randomly selected from the center line of the target boundary lane, for example 、 The starting point and end point of the lane centerline can be taken separately. with by 、 The formula for the left and right orientation of a line determined by a point is as follows:

[0081]

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

[0083] In addition, the lateral distance of the target vehicle relative to the target boundary lane satisfies the following formula:

[0084]

[0085] in, That is, the lateral distance of the target vehicle relative to the target boundary lane, for example, the lateral distance of the target vehicle relative to the left boundary lane d_left_bound_lane, or the lateral distance of the target vehicle relative to the right boundary lane d_right_bound_lane.

[0086] For example, Figure 2 Schematic diagram of deviation state provided by exemplary embodiment of the present application. 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", and 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", and 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", and 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 on 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 a lane half-width threshold comparison mechanism and introducing zero-value truncation processing, the false alarms of small offsets 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 enhancing the robustness and reliability in various road scenarios.

[0088] Figure 3 It 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: Determine the relative distance between the target vehicle and the starting point of the import lane based on the lane information.

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

[0092] If not, execute S302;

[0093] If so, execute S304.

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

[0095] S305: Determine the deviation direction of the target vehicle relative to the left boundary lane.

[0096] S306: Determine whether the deviation direction is left.

[0097] If yes, execute S307;

[0098] If not, execute S310.

[0099] S307: Determine a 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 whether the left lateral offset distance is greater than 0.

[0102] If yes, execute S309;

[0103] If not, execute S316.

[0104] S309: Determine that a deviation occurs, the deviation direction is left, and the left lateral offset distance is the lateral offset distance.

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

[0106] S311. Determine the deviation direction of the target vehicle relative to the right boundary lane.

[0107] S312: Determine whether the deviation direction is right.

[0108] If yes, execute S313;

[0109] If not, execute S16.

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

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

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

[0113] If yes, execute S315;

[0114] If not, execute S316.

[0115] S315: Determine that a deviation occurs, the deviation direction is right, and the right lateral offset distance is the lateral offset distance.

[0116] S316. Determine that no deviation occurs.

[0117] It should be noted that the above-mentioned S304 determining the left boundary lane in the same direction as the import lane is only an example. S310 can also be executed first to determine the right boundary lane in the same direction as the import 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] First, by obtaining lane information for the first upcoming intersection ahead based on the target vehicle's navigation path, the system enables refined monitoring of the vehicle's driving status. This not only accurately determines whether the vehicle has deviated, as well as the direction and lateral offset distance, but also derives a yaw warning factor by comprehensively quantifying driving speed, relative distance, and lateral offset distance. This yaw warning factor is then used to determine whether to trigger a yaw warning. This multi-dimensional parameter-integrated warning mechanism significantly improves the ability to predict yaw risk and triggers a warning before the vehicle actually deviates. This effectively addresses the lag issue of traditional navigation systems, which can only provide after-the-fact warnings. This significantly enhances the early warning capability for intersection yaw, thereby effectively reducing the risk of yaw caused by incorrect lane selection. This is crucial for improving intersection traffic efficiency, reducing traffic congestion and accidents, and providing more proactive safety assurance for drivers.

[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 of deviation risk is achieved; dynamic judgment based on the threshold difference can match the corresponding warning intensity, which not only reduces excessive warning interference in low-risk scenarios, but also ensures that sufficiently strong warnings are provided in high-risk situations, thereby improving driving safety while optimizing the driving experience.

[0121] Third, by searching adjacent lanes of the same turning type step by step along the target direction starting from the entrance lane, it can accurately identify the boundary lane that matches the current driving intention in complex intersection topology structures, significantly improving lane matching accuracy compared to the fixed-distance search method. Using turning type consistency as the recursive termination condition can effectively eliminate interference from adjacent opposite-direction lanes, ensuring that the final target boundary lane maintains directional consistency with the vehicle's actual driving path. This recursive mechanism can not only adapt to intersection scenarios with multiple lanes extending in parallel (such as continuous left-turn lanes), but also accurately handle lane gradients or bifurcations, 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 on the lane centerline and the vehicle position, the vehicle's lateral offset distance and deviation direction relative to the lane centerline can be accurately calculated, significantly improving detection accuracy in complex curved scenarios. In addition, the use of a lane half-width threshold comparison mechanism and the introduction of zero-value truncation processing can effectively filter out minor offset false alarms caused by lane line recognition errors or positioning jitter. At the same time, the direct correlation between the actual vehicle position and lane geometry through vector operations is not only applicable to straight lanes, but also accurately adapts to deviation detection in curved lanes, greatly improving the robustness and reliability in various road scenarios.

[0123] The following are device embodiments of the present application, which can be used to implement the method embodiments of the present application. For details not disclosed in the device embodiments of the present application, please refer to the method embodiments of the present application.

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

[0125] An acquisition module 41 is configured to acquire lane information of an entrance lane of a first navigation intersection ahead based on the navigation path of the target vehicle;

[0126] A first determining module 42 is configured to determine a deviation state of the target vehicle based on the lane information, where the deviation state includes whether a deviation occurs, and a deviation direction and a lateral deviation distance when the deviation occurs;

[0127] A second determination module 43 is configured to determine a yaw warning factor of the target vehicle based on the target vehicle's speed, relative distance, and lateral offset distance when the target vehicle deviates, where the relative distance is the distance from the target vehicle to the starting point of the import lane;

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

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

[0130] In one possible implementation, the second determination 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 safety distance of the target vehicle from the import lane; add half the lane width of the import lane to the remaining safety distance to obtain a reference distance; and determine the ratio of the lateral offset distance to the reference distance as a yaw warning factor.

[0131] In one possible implementation, the first determination module 42 may also be used to: determine the target boundary lane in the first navigation intersection ahead that is in the same direction as the import lane 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 determination module 42 may also be configured to: take the import lane as the starting lane, and recursively search along the target direction for a lane in the first navigation intersection ahead that has the same lane turning type as the import lane, until the lane turning type is different from the lane turning type of the import lane, whereupon the recursive search stops, and the last lane that has the same lane turning type as the import lane is determined as the target boundary lane.

[0133] In one possible implementation, the first determination module 42 may also be used to: obtain two reference coordinate points on the lane centerline 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 lane centerline of the target boundary lane using operations between the position coordinates and the vector formed by the two reference coordinate points; subtract the lateral distance from half the lane width of the target boundary lane 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 positive or negative value of the lateral offset distance.

[0134] In one possible implementation, the yaw warning includes the deviation direction, 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 a level corresponding to the interval range according to the interval range to which the threshold difference belongs.

[0135] The intersection deviation warning device provided in the embodiment of the present application can implement the technical solution shown in the above-mentioned intersection deviation warning method embodiment. Its implementation principle and beneficial effects are similar and will not be repeated here.

[0136] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all optional embodiments, and the actions and modules involved are not necessarily required by this application.

[0137] It should be further noted that, although the various steps in the flowchart are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps may be performed in other orders. Moreover, at least a portion of the steps in the flowchart may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily performed at the same time, but may be performed at different times. The execution order of these sub-steps or stages is not necessarily to be performed in sequence, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0138] It should be noted that the above-mentioned device embodiments are merely illustrative, and the device of the present application may also be implemented in other ways. Furthermore, it should be understood that the division of the various modules of the above-mentioned device is merely a division of logical functions. In actual implementation, they may be fully or partially integrated into a single physical entity, or they may be physically separated. Furthermore, these modules may all be implemented in the form of software called by a processing element; or all be implemented in the form of hardware; or some modules may be implemented in the form of software called by a processing element, and some modules may be implemented in the form of hardware. For example, the yaw warning module may be a separate processing element, or it may be integrated into a chip of the above-mentioned device. Furthermore, it may be stored in the form of program code in the memory of the above-mentioned device, and called and executed by a processing element of the above-mentioned device. The implementation of other modules is similar. Furthermore, these modules may all or partly be integrated together, or implemented independently. The processing element here may be an integrated circuit with signal processing capabilities. During implementation, each step of the above-mentioned method or each of the above modules may be completed by hardware integrated logic circuits in the processor element or by software instructions.

[0139] For example, the above modules may 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). For another example, when a module is implemented by scheduling program code through a processing element, the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processor capable of calling program code. For another example, these modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0140] In the above embodiments, all or part of the embodiments can be implemented using software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of 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 processes or functions according to the embodiments of the present application are 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, the 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, optical fiber, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that integrates one or more available media. Available media may be magnetic media (eg, floppy disks, hard disks, magnetic tapes), optical media (eg, Digital Video Discs (DVDs)), or semiconductor media (eg, solid state disks (SSDs)).

[0141] Figure 5 This is a schematic diagram of the structure of an electronic device provided by an exemplary embodiment of the present application. Figure 5 As shown, the electronic device 50 of this embodiment includes:

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

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

[0144] Optionally, the memory 52 may be independent or integrated with the processor 51 .

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

[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 the present application. Specifically, when implementing the intersection deviation warning method described in the aforementioned method embodiment, the electronic device may be, for example, an electronic device with processing capabilities, such as a server.

[0147] Optionally, the electronic device may further include a communication interface 53. In a specific implementation, if the communication interface 53, memory 52, and processor 51 are implemented independently, the communication interface 53, memory 52, and processor 51 may be interconnected via a bus and communicate with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be categorized as address buses, data buses, control buses, and so on, but this does not necessarily mean that there is only one bus or only one type of bus.

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

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

[0150] An embodiment of the present application also provides a computer-readable storage medium, which stores computer execution instructions. When the computer execution instructions are executed, they are used to implement the method steps in the above method embodiment. The specific implementation method and technical effects are similar and will not be repeated here.

[0151] The computer-readable storage medium described above can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The computer-readable storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0152] An exemplary readable storage medium is coupled to the processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium may also be an integral part of the processor. The processor and readable storage medium may be located in an application-specific integrated circuit. Of course, the processor and readable storage medium may also be present as discrete components in the intersection deviation warning device.

[0153] An embodiment of the present application also provides a computer program product, including a computer program. When the computer program is executed, the method steps in the above method embodiment are implemented. The specific implementation method and technical effects are similar and will not be repeated here.

[0154] In the above embodiments, the description of each embodiment has its own emphasis. For parts not described in detail in a particular embodiment, please refer to the relevant description of other embodiments. The technical features of the above embodiments can be combined in any way. To keep the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0155] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of the present application and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

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

Claims

1. A method for warning of deviation at an intersection, characterized in that: include: Based on the navigation path of the target vehicle, the lane information of the entrance lane of the first navigation intersection ahead is obtained; Determining a deviation state of the target vehicle based on the lane information, the deviation state including whether a deviation occurs, and a deviation direction and a lateral deviation distance when the deviation occurs; If the target vehicle deviates, a yaw warning factor of the target vehicle is determined based on the target vehicle's speed, relative distance, and lateral offset distance, where the relative distance is the distance from the target vehicle to the starting point of the import lane; When the yaw warning factor is greater than a preset yaw warning triggering threshold, a yaw warning for the target vehicle is triggered.

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

3. The intersection deviation warning method according to claim 1, characterized in that: The determining of the yaw warning factor of the target vehicle based on the traveling speed, the relative distance, and the lateral offset distance of the target vehicle includes: determining a safety barrier distance of the target vehicle based on the driving speed; Subtracting the relative distance from the safety barrier distance to obtain a first distance difference; Taking the maximum value of the first distance difference and 0 as the remaining safe distance between the target vehicle and the import lane; Adding half the lane width of the import lane to the remaining safety distance to obtain a reference distance; A ratio of the lateral offset distance to the reference distance is determined as the yaw warning factor.

4. The method for warning of a course deviation at an intersection according to any one of claims 1 to 3, characterized in that: The determining the deviation state of the target vehicle based on the lane information includes: Determining, based on the lane information, a target boundary lane at the first navigation intersection ahead that is in the same direction as the entrance lane; The deviation state of the target vehicle is determined based on the position coordinates of the target vehicle and the lane information of the target boundary lane.

5. The intersection deviation warning method according to claim 4, characterized in that: The determining, based on the lane information, a target boundary lane in the first navigation intersection ahead and in the same direction as the entrance lane, includes: Taking the import lane as the starting lane, recursively search along the target direction for a lane in the first navigation intersection ahead with the same lane turning type as the import lane. The recursive search stops when the lane turning type is different from the lane turning type of the import lane, and the last lane with the same lane turning type as the import lane is determined as the target boundary lane.

6. The intersection deviation warning method according to claim 4, characterized in that: The 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 includes: Obtaining two reference coordinate points on the lane 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 a lateral distance between the target vehicle and a lane centerline of the target boundary lane by using an operation between the position coordinates and a vector formed by the two reference coordinate points; subtracting the lateral distance from half the lane width of the target boundary lane to obtain a second distance difference; The maximum value between the second distance difference and 0 is taken as the lateral offset distance; Whether the target vehicle deviates is determined based on the positive or negative condition of the lateral offset distance.

7. The intersection deviation warning method according to any one of claims 1 to 3, characterized in that: The yaw warning includes the deviation direction, the lateral offset distance, and the relative distance. When the yaw warning factor is greater than a preset yaw warning triggering threshold, triggering a yaw warning for the target vehicle includes: determining a threshold difference between the yaw warning factor and the yaw warning triggering threshold; According to the interval range to which the threshold difference value belongs, a yaw warning of a level corresponding to the interval range is triggered.

8. A road intersection deviation warning device, characterized in that: include: An acquisition module, for acquiring lane information of an import lane of a first navigation intersection ahead based on a navigation path of a target vehicle; A first determining module is configured to determine a deviation state of the target vehicle based on the lane information, wherein the deviation state includes whether a deviation occurs, and a deviation direction and a lateral offset distance when the deviation occurs; a second determining module, configured to determine a yaw warning factor of the target vehicle based on a driving speed, a relative distance, and the lateral offset distance of the target vehicle when the target vehicle deviates, wherein the relative distance is the distance from the target vehicle to the starting point of the import lane; 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.

9. An electronic device, characterized in that: include: a processor, and a memory communicatively connected to the processor; The memory is used to store computer-executable instructions; The processor is configured to execute the computer-executable instructions to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed.

11. A computer program product comprising a computer program, characterized in that When the computer program is executed, the method according to any one of claims 1 to 7 is implemented.

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