Bus stop early warning method and early warning equipment based on security and protection monitoring

Abstract

The invention discloses a bus stop early warning method and early warning equipment based on security and protection monitoring, and relates to the field of security and protection monitoring and early warning. According to the method, danger, alert and driving areas are divided through road marking lines, abnormal vehicles are marked in combination with a speed mean value, an acceleration standard deviation and trajectory curve smoothness multi-dimensional judgment logic, and vertical collision prediction speeds and contact prediction positions of the abnormal vehicles are calculated through a motion trajectory equation. And dynamically adjusting the early warning duration according to the passenger density and updating an indicator light flicker area in real time. Therefore, passengers waiting for the bus in the bus station can identify the dangerous source direction in time under the condition that the moving bus deviates from the normal driving track and collides with the bus station due to misoperation, mechanical failure or sudden illness of a driver.

Description

Technical Field

[0001] The present application relates to the field of security monitoring and early warning, and in particular to a bus stop early warning method and early warning device based on security monitoring. Background Art

[0002] With the acceleration of urbanization, the scale of cities continues to expand, the population density gradually increases, and the setting up of bus stops has become increasingly common. At the same time, the safety issues of passengers waiting at bus stops have gradually become prominent.

[0003] Currently, to ensure the safety of passengers waiting at bus stops under overpasses, related technologies primarily rely on installing physical protective facilities such as guardrails and speed bumps around the stops. However, physical protective facilities can only passively protect waiting passengers. To proactively prevent danger, a system based on onboard cameras and onboard maps can detect when a vehicle is approaching a risk point (such as a bus stop or overpass entrance). The system then warns pedestrians by honking the horn or flashing the headlights, and notifies the driver via voice or text messages from within the vehicle that the vehicle is about to pass through a dangerous area.

[0004] However, passengers waiting at bus stops usually focus their attention on their mobile phones or electronic bus stop signs. In complex traffic environments, multiple vehicles may sound their horns at the same time. If a vehicle deviates from its normal driving trajectory and collides with the bus stop due to operational errors, mechanical failures, or sudden illness of the driver, it will be difficult for waiting passengers at the stop to identify the direction of the danger source, which will seriously threaten passenger safety. Summary of the Invention

[0005] The present application provides a bus stop early warning method and early warning device based on security monitoring, which is used to enable waiting passengers at a bus stop to identify the direction of the danger source when a vehicle deviates from its normal driving trajectory and collides with a bus stop due to operating error, mechanical failure or sudden illness of the driver.

[0006] In the first aspect, the present application provides a bus stop early warning method based on security monitoring, comprising: the early warning device divides the bus stop area into a dangerous area, a warning area and a driving area based on the recognition of road markings by the monitoring camera, the dangerous area is the area where the platform itself is located, the warning area is the single lane area closest to the bus stop, and the driving area is the other lane area within the monitoring range that is not the warning area; the early warning device marks as abnormal vehicles any moving vehicle whose average speed in the driving area within a first preset time period is greater than or equal to a preset speed threshold and whose acceleration standard deviation is greater than or equal to a preset standard deviation threshold. The first preset time period is based on the corresponding The moment when the direction angle of the moving vehicle changes from pointing outside the danger zone to pointing into the danger zone is determined by extending forward and backward from the midpoint; when the direction angle of the abnormal vehicle still points to the danger zone when it crosses the boundary of the warning area, the early warning device calculates the vertical collision prediction speed and contact prediction position when the abnormal vehicle contacts the danger zone based on the current position, speed, acceleration of the abnormal vehicle and the distance from the danger zone after a second preset time period; when it is determined that the vertical collision prediction speed is greater than 0, the early warning device controls the indicator light at the contact prediction position in the bus stop to flash red, and the indicator light is arranged along the length direction of the bus stop.

[0007] By adopting the above technical solution, a complete early warning chain is realized from area division to abnormal vehicle identification and then to collision prediction. It can accurately locate vehicles in dangerous areas that may collide, and warn in advance through flashing red indicator lights, effectively improving the accuracy and timeliness of bus stop security monitoring and reducing collision risks.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the early warning device marks as abnormal vehicles those moving vehicles whose average speed in the driving area within a first preset time period is greater than or equal to a preset speed threshold and whose acceleration standard deviation is greater than or equal to a preset standard deviation threshold, specifically including: after the moving vehicle enters the driving area, the early warning device identifies the moving vehicle based on the monitoring video and constructs a driving status table for the mobile vehicle, the driving status table is the position, direction angle, speed, and acceleration of the moving vehicle at different times after entering the monitoring area; when the direction angle of the moving vehicle changes from pointing outside the dangerous area to pointing inside When the vehicle is in a dangerous area, the early warning device calculates the average speed and acceleration standard deviation of the moving vehicle in the driving area within the first preset time period based on the driving status table; when the average speed of the moving vehicle in the driving area within the first preset time period is greater than or equal to the preset speed threshold and the acceleration standard deviation is greater than or equal to the preset standard deviation threshold, the early warning device marks the moving vehicle as an abnormal vehicle; when the average speed of the moving vehicle in the driving area within the first preset time period is less than the preset speed threshold and the acceleration standard deviation is less than the preset standard deviation threshold, the early warning device marks the moving vehicle as a normal vehicle.

[0009] By employing this technical solution, when a moving vehicle enters a driving area, the warning device identifies it based on surveillance video and constructs a driving status table containing its position, azimuth, speed, and acceleration at different times, comprehensively recording the vehicle's driving status. This detailed driving status table, along with criteria for judging mean speed and standard deviation of acceleration, improves the accuracy of abnormal vehicle identification, avoids misjudgments, and provides a reliable basis for subsequent warnings, enabling the warning system to more accurately identify potentially dangerous vehicles.

[0010] In combination with some embodiments of the first aspect, in some embodiments, before the step of the early warning device marking the moving vehicle as a normal vehicle when the average speed of the moving vehicle in the driving area within the first preset time period is less than a preset speed threshold and the acceleration standard deviation is less than a preset standard deviation threshold, the method also includes: when the average speed of the moving vehicle in the driving area within the first preset time period is greater than or equal to the preset speed threshold and the acceleration standard deviation is less than the preset standard deviation threshold, the early warning device determines the smoothness of the trajectory curve of the moving vehicle within the first preset time period based on the driving status table, and the trajectory curve smoothness refers to the degree to which the driving trajectory of the moving vehicle within the first preset time period deviates from a straight line or a uniform curve; when the smoothness of the trajectory curve of the moving vehicle within the first preset time period is greater than or equal to the preset smoothness threshold, the early warning device marks the moving vehicle as an abnormal vehicle.

[0011] By adopting the above technical solution, when the average speed of a moving vehicle is greater than or equal to a preset speed threshold and the acceleration standard deviation is greater than a preset standard deviation threshold, the early warning device determines the smoothness of its trajectory curve based on the driving status table. When the trajectory curve smoothness is greater than or equal to the preset smoothness threshold, the vehicle is marked as abnormal. This supplementary step adds a judgment dimension for the smoothness of the trajectory curve, and combines it with the speed and acceleration standard deviation to more comprehensively evaluate the vehicle's driving status. Some vehicles may have complex combinations of speed and acceleration standard deviations, which may result in missed judgments. The judgment of trajectory smoothness can capture abnormalities in the vehicle's driving trajectory, further improving the accuracy of abnormal vehicle marking, reducing missed judgments, and making the early warning system more reliable.

[0012] In combination with some embodiments of the first aspect, in some embodiments, when the direction angle of the abnormal vehicle still points to the dangerous area when the abnormal vehicle crosses the boundary of the warning area, the early warning device calculates the vertical collision prediction speed and contact prediction position of the abnormal vehicle when it contacts the dangerous area based on the current position, speed, acceleration and distance from the dangerous area of the abnormal vehicle after a second preset time period, specifically including: when the direction angle of the abnormal vehicle still points to the dangerous area when the abnormal vehicle crosses the boundary of the warning area, the early warning device fits the position, speed, acceleration and distance from the dangerous area within a third preset time period into a motion trajectory equation after the second preset time period, and the third preset time period is determined by extending forward from the moment when the second preset time period ends; the early warning device calculates the coordinates of the intersection of the abnormal vehicle and the boundary of the dangerous area based on the motion trajectory equation; the early warning device calculates the vertical collision prediction speed and contact prediction position of the abnormal vehicle when it contacts the dangerous area based on the tangent vector of the trajectory equation at the intersection coordinates.

[0013] By adopting the above technical solution and calculating the collision prediction method by fitting the motion trajectory equation, the various parameters of the vehicle motion are fully utilized, making the prediction more consistent with the actual motion laws of the vehicle, and improving the calculation accuracy of the vertical collision prediction speed and contact prediction position, providing more accurate data support for subsequent accurate warnings, so that the indicator light can more accurately flash red warnings at the contact prediction position.

[0014] In combination with some embodiments of the first aspect, in some embodiments, before the step of fitting the position, speed, acceleration and distance from the dangerous area of the abnormal vehicle within a third preset time period after the second preset time period into a motion trajectory equation, the method further includes: when the direction angle of the abnormal vehicle still points to the dangerous area when the abnormal vehicle crosses the boundary of the warning area, the early warning device calculates the vertical collision prediction speed and contact prediction position of the abnormal vehicle when it contacts the dangerous area based on the motion trajectory equation of the abnormal vehicle within a fourth preset time period, and the fourth preset time period is determined by extending forward from the moment when the abnormal vehicle crosses the boundary of the warning area as the end point; when the abnormal vehicle When the vertical collision prediction speed within the fourth preset time period is greater than 0 and the density of waiting passengers at the contact prediction position is greater than or equal to the preset waiting passenger density threshold, the early warning device calculates the critical vertical collision time of the abnormal vehicle in the danger zone, and the critical vertical collision time in the danger zone refers to the time required for the abnormal vehicle to be at a vertical distance from the boundary of the danger zone to be 0; when the critical vertical collision time of the abnormal vehicle in the danger zone is greater than the second preset time period, the early warning device reduces the second preset time period to the fourth preset time period; when the critical vertical collision time of the abnormal vehicle in the danger zone is less than or equal to the second preset time period, the early warning device controls the indicator light at the contact prediction position in the bus stop to flash red.

[0015] By adopting the above technical solution, the density of waiting passengers is taken into consideration. When an abnormal vehicle may pose a danger to high-density waiting passengers, the second preset duration is dynamically adjusted according to the vertical collision critical time, making the warning time more reasonable. It can not only provide timely warnings, but also avoid warnings that are too early or too late, thereby improving the effectiveness and pertinence of warnings and better protecting the safety of waiting passengers.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes: The warning device controls the indicator light at the contact prediction position in the bus stop to flash red, and continuously calculates the vertical collision prediction speed and contact prediction position of the abnormal vehicle when it contacts the dangerous area; when the vertical collision prediction speed of the abnormal vehicle when it contacts the dangerous area is less than or equal to 0, the warning device turns off the indicator light; when the vertical collision prediction speed is still greater than 0, the warning device continuously adjusts the area where the indicator light flashes red according to the change of the contact prediction position of the abnormal vehicle.

[0017] By implementing this technical solution, the warning system can track changes in vehicle status and collision risk in real time. As the vehicle moves, the predicted contact location may change. This allows the indicator light flashing area to be adjusted promptly, ensuring the warning is always targeted at the most likely collision location. This improves the real-time and accuracy of warnings, making them more effective and enhancing their effectiveness.

[0018] In combination with some embodiments of the first aspect, in some embodiments, after the step of the warning device continuously adjusting the area in which the indicator light flashes red according to the change of the predicted contact position of the abnormal vehicle when the vertical collision prediction speed is still greater than 0, the method also includes: after the abnormal vehicle avoids the dangerous area and leaves the monitoring area, the warning device marks the abnormal vehicle as a dangerous vehicle and sends an alarm message to the surrounding warning devices, and the alarm information includes information such as the license plate number of the dangerous vehicle, the vehicle type, and the driving status table in the monitoring area.

[0019] By implementing this technical solution, early warning information can be shared and linked across surrounding early warning devices. Upon receiving the alert, surrounding early warning devices can proactively monitor the dangerous vehicle and take timely early warning measures when it enters the surrounding monitoring area. This expands the early warning range, forms a more extensive security monitoring network, and improves the coordination and security of the overall security monitoring system.

[0020] In a second aspect, an embodiment of the present application provides an early warning device, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the early warning device to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions, which, when run on an early warning device, enables the early warning device to execute the method described in the first aspect and any possible implementation of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium comprising instructions. When the instructions are executed on an early warning device, the early warning device executes the method described in the first aspect and any possible implementation of the first aspect.

[0023] It is understandable that the warning device provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the methods provided in the embodiments of the present application. Therefore, the beneficial effects that can be achieved can be referenced to the beneficial effects of the corresponding methods and will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. After a moving vehicle enters the driving area, the warning device identifies the moving vehicle based on the surveillance video and constructs a driving status table containing the position, direction angle, speed, acceleration and other data of the moving vehicle at different times. Therefore, it can comprehensively record the vehicle's driving status. With the help of a detailed driving status table and the judgment criteria of the speed mean and acceleration standard deviation, the accuracy of abnormal vehicle marking is improved, thereby providing a reliable basis for subsequent warnings and enabling the warning system to more accurately identify potentially dangerous vehicles.

[0025] 2. Due to the adoption of a mechanism for dynamically adjusting the second preset duration based on the vertical collision critical time, when a moving vehicle may pose a danger to a crowded area of waiting passengers at a bus stop, the second preset duration is dynamically adjusted according to the vertical collision critical time of the moving vehicle, making the warning time more reasonable. This can not only provide timely warnings, but also avoid warnings that are too early or too late, thereby improving the effectiveness and pertinence of warnings and better protecting the safety of waiting passengers.

[0026] 3. Due to the sharing and linkage mechanism of early warning information among surrounding early warning devices, the surrounding early warning devices can pay attention to the dangerous vehicle in advance after receiving the alarm information, and then take early warning measures in time when it enters the surrounding monitoring area, expanding the early warning range, forming a wider security monitoring network, and improving the coordination and safety of the overall security monitoring system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a scenario diagram of a bus stop early warning method based on security monitoring in an embodiment of the present application.

[0028] Figure 2 This is a flow chart of a bus stop early warning method based on security monitoring in an embodiment of the present application.

[0029] Figure 3 This is another flow chart of a bus stop early warning method based on security monitoring in an embodiment of the present application.

[0030] Figure 4 This is a schematic diagram of the physical device structure of the early warning device in the embodiment of the present application. DETAILED DESCRIPTION

[0031] The terms used in the following examples of the present application are for the purpose of describing specific embodiments only and are not intended to limit the present application. As used in the specification and appended claims of the present application, the singular expressions "a," "an," "said," "above," "the," and "this" are intended to include plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to and encompasses any or all possible combinations of one or more of the listed items.

[0032] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of the technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of this application, unless otherwise specified, "plurality" means two or more.

[0033] The embodiments of the present application provide a bus stop warning method and warning device based on security monitoring, which is used to enable waiting passengers at a bus stop to identify the direction of the danger source when a vehicle deviates from its normal driving trajectory and collides with a bus stop due to operational error, mechanical failure or sudden illness of the driver.

[0034] The following describes a bus stop warning method based on security monitoring in an embodiment of the present application: See also Figure 1 , which is a scenario diagram of a bus stop warning method based on security monitoring in an embodiment of the present application.

[0035] like Figure 1 As shown, the early warning device first divides the bus stop area into a danger zone, a warning zone, and a driving zone based on the surveillance camera's recognition of road markings. The danger zone is the area where the platform itself is located, the warning zone is the single lane area closest to the bus stop, and the driving zone is other lane areas within the monitoring range that are not in the warning zone.

[0036] The early warning device then obtains data such as the direction angle, speed, and acceleration of moving vehicles in the driving area in real time. When it detects that the direction angle of a moving vehicle changes from pointing outside the danger zone to pointing towards the danger zone, that is, at time T, the early warning device takes time T as the midpoint and extends forward and backward to obtain a first preset time length, and then calculates the mean speed and acceleration standard deviation of the vehicle within the first preset time length, compares the mean speed with the preset speed threshold, and compares the acceleration standard deviation with the preset standard deviation threshold. If the mean speed is greater than or equal to the preset speed threshold and the acceleration standard deviation is greater than or equal to the preset standard deviation threshold, the vehicle is marked as an abnormal vehicle.

[0037] When an abnormal vehicle crosses the boundary of the warning area and its direction angle is still pointing to the danger zone, the early warning device starts timing. After the second preset time, it obtains data such as the abnormal vehicle's current position, speed, acceleration, and distance from the danger zone. Then, based on this data, it calculates the vertical collision prediction speed and contact prediction position when the abnormal vehicle contacts the danger zone.

[0038] Finally, when it is determined that the vertical collision prediction speed of the abnormal vehicle is greater than 0, the warning device controls the indicator light at the contact prediction position in the bus stop to flash red.

[0039] See also Figure 2 , which is a flow chart of a bus stop warning method based on security monitoring in an embodiment of the present application.

[0040] S201. The early warning device divides the bus stop area into a danger zone, a warning zone, and a driving zone based on the recognition of road markings by a surveillance camera.

[0041] Surveillance cameras are installed around bus stops, shooting downward at a 30-45° angle at an altitude of 8-12 meters. These cameras capture road image information and acquire road scene data through optical imaging principles. Road markings delineate functional areas on the road and serve as a crucial basis for early warning systems to demarcate zones. The danger zone is the area surrounding the bus platform itself, serving as the core area for passenger boarding and alighting. The warning zone is the dedicated lane closest to the bus stop. The driving zone refers to the lanes within the monitoring area, other than the warning zone, and is the primary area for normal vehicle operation.

[0042] Specifically, the early warning system first uses surveillance cameras to collect road image data, then identifies and analyzes the road markings in the image. Based on the position and shape of the markings, it accurately divides the bus stop area into a danger zone, a warning zone, and a travel zone. During this process, it is necessary to ensure that the surveillance camera's installation position and angle fully cover the relevant area of the bus stop, and accurately identify the type and characteristics of the road markings to ensure the accuracy of the zone division. For example, if a surveillance camera captures a solid line in front of the platform, the area near the platform is designated as a danger zone, the lane containing the solid line is designated as a warning zone, and all other lanes are designated as travel zones.

[0043] In some embodiments, bus stop area division can be achieved through image recognition algorithms. For example, warning devices and surveillance cameras are first activated and put into operation. Then, image recognition algorithms are used to process road images captured by the surveillance cameras to identify road markings. Finally, based on the location of the markings and pre-set division rules, the bus stop area is divided into a danger zone, a warning zone, and a travel zone.

[0044] In other embodiments, the surveillance camera can be calibrated first to ensure that the images it captures accurately reflect the actual road conditions. A machine learning model is then used to identify and classify road markings. Based on the identification results and pre-set area division criteria, the scope of each area is determined and divided.

[0045] It is understandable that other methods may be used to implement the regional division of bus stops, such as combining GPS positioning and road electronic map information to assist in regional division, etc., which are not limited here.

[0046] S202. The early warning device marks as abnormal vehicles any moving vehicles whose average speed in the driving area within a first preset time period is greater than or equal to a preset speed threshold and whose acceleration standard deviation is greater than or equal to a preset standard deviation threshold.

[0047] Among them, the first preset time period refers to a period of time determined by extending forward and backward from the moment when the direction angle of the corresponding moving vehicle changes from pointing outside the danger zone to pointing into the danger zone as the midpoint, and is used to limit the time range for analyzing vehicle driving data. The mean speed represents the average driving speed of the moving vehicle within the first preset time period. The preset speed threshold is a set value used to determine whether the vehicle speed is abnormal. The acceleration standard deviation is used to indicate the degree of fluctuation of the acceleration of the moving vehicle within the first preset time period. The preset standard deviation threshold is a set value for determining whether the acceleration fluctuation is abnormal. Moving vehicles refer to various types of vehicles traveling on the road. Abnormal vehicles refer to vehicles that meet the conditions that the mean speed is greater than or equal to the preset speed threshold and the acceleration standard deviation is greater than or equal to the preset standard deviation threshold. For example, when a car drives near a bus stop, its direction angle changes from away from the platform to pointing towards the platform. Taking this moment as the midpoint, a period of time is extended forward and backward to form a first preset duration. During this period, if the average speed of the car reaches the preset speed threshold and the acceleration standard deviation is greater than or equal to the preset standard deviation threshold, it means that the vehicle speed turning process is abrupt or the vehicle stability is poor. Normal vehicles usually slow down when turning, so the car will be marked as an abnormal vehicle.

[0048] Specifically, the early warning device acquires data such as the direction angle, speed, and acceleration of moving vehicles in the driving area in real time. When it detects that the direction angle of a moving vehicle changes from pointing outside the danger zone to pointing into the danger zone, it determines that moment as the midpoint, extends it forward and backward to obtain a first preset duration, and then calculates the mean speed and standard deviation of the acceleration of the vehicle within the first preset duration. The mean speed is compared with the preset speed threshold, and the standard deviation of the acceleration is compared with the preset standard deviation threshold. If the mean speed is greater than or equal to the preset speed threshold and the standard deviation of the acceleration is greater than or equal to the preset standard deviation threshold, the vehicle is marked as an abnormal vehicle. For example, when a vehicle is driving towards a bus stop, its direction angle changes from pointing outside the danger zone to pointing into the danger zone. The early warning device promptly captures this change, determines the first preset duration, analyzes the driving data of the bus during this period, and determines whether to mark it as an abnormal vehicle.

[0049] In some embodiments, a moving vehicle can be marked as an abnormal vehicle based on a vehicle data collection system. First, a vehicle data collection system is established to collect data such as the vehicle's heading angle, speed, and acceleration in real time within the driving area. A heading angle change detection module is then set up to monitor changes in the vehicle's heading angle in real time. When the heading angle changes from pointing outside the danger zone to pointing into the danger zone, the moment is recorded. A first preset duration is then determined based on this moment. Data for the vehicle within this first preset duration is retrieved from the data collection system, and the mean speed and standard deviation of acceleration are calculated. Finally, the calculated results are compared with preset thresholds to determine whether the vehicle is marked as an abnormal vehicle.

[0050] In other embodiments, a sensor network can be used to monitor vehicles within a driving area and acquire relevant vehicle data. A real-time data processing algorithm is employed to analyze vehicle heading angles in real time and detect changes in heading angles. When a heading angle change is detected, a data extraction module is triggered to extract data from the vehicle within a first preset time period. A calculation module then calculates the mean velocity and standard deviation of acceleration, compares them with preset thresholds, and labels abnormal vehicles.

[0051] It is understandable that other methods can also be used to complete the marking of abnormal vehicles, such as analyzing and marking the vehicle data sent by the vehicle terminal, etc., which are not limited here.

[0052] S203. When the direction angle of the abnormal vehicle still points to the danger zone when it crosses the boundary of the warning area, the early warning device calculates the vertical collision prediction speed and contact prediction position of the abnormal vehicle when it contacts the danger zone after a second preset time period.

[0053] Among them, the abnormal vehicle is a vehicle that has been marked as abnormal in S202. The warning area boundary refers to the dividing line between the warning area and other areas. The direction angle pointing to the danger area indicates that the vehicle is traveling in the direction of the danger area. The second preset time length refers to the waiting period after the abnormal vehicle crosses the warning area boundary. The vertical collision prediction speed refers to the predicted collision speed in the vertical direction when the abnormal vehicle contacts the danger area. The contact prediction position refers to the specific position where the abnormal vehicle is predicted to contact the danger area. For example, when a vehicle marked as abnormal crosses the warning area boundary, the direction angle still points to the danger area. After the second preset time length, the early warning device obtains the vehicle's position, speed, acceleration, and distance to the danger area at this time, and predicts the vertical collision speed and contact position of the vehicle when it contacts the danger area through calculation.

[0054] Specifically, when an abnormal vehicle crosses the boundary of the warning area and its heading angle is still pointing toward the danger zone, the warning device begins counting. After a second preset time, it obtains data such as the abnormal vehicle's current position, speed, acceleration, and distance from the danger zone. Based on this data, it then calculates the predicted vertical collision speed and contact position of the abnormal vehicle at the time of contact with the danger zone. For example, if an abnormal vehicle crosses the boundary of the warning area and continues toward the danger zone without changing its heading angle, the warning device will calculate the position and vertical collision speed at which the abnormal vehicle may contact the danger zone based on the vehicle's real-time data after the second preset time.

[0055] In some embodiments, the predicted vertical collision velocity and predicted contact position can be calculated based on a collision prediction algorithm. First, sensors are placed at the boundary of the warning area to detect whether an abnormal vehicle has crossed the boundary and its azimuth. When an abnormal vehicle is detected crossing the boundary and its azimuth is pointing toward the danger zone, a timer is started. After a second preset time, the vehicle's current position is acquired through a positioning system, its speed is acquired through a speed sensor, its acceleration is acquired through an acceleration sensor, and its distance to the danger zone is calculated. Finally, a collision prediction algorithm is used to calculate the predicted vertical collision velocity and predicted contact position based on this data.

[0056] In other embodiments, a video surveillance system can be used to track unusual vehicles. When an unusual vehicle crosses the boundary of a warning zone without changing its azimuth, the moment is recorded. A timer is then started, and after a second preset duration, the vehicle's current position is determined using image recognition technology. Combined with previously collected velocity and acceleration data, the distance to the danger zone is calculated. A physical kinematic model is then used to calculate the predicted vertical collision velocity and contact position.

[0057] It is understandable that other methods can also be used to calculate the vertical collision prediction speed and contact prediction position, such as combining vehicle data provided by the vehicle navigation system and monitoring data of roadside equipment for calculation, which is not limited here.

[0058] S204: When it is determined that the vertical collision prediction speed is greater than 0, the warning device controls the indicator light at the contact prediction position in the bus stop to flash red.

[0059] The vertical collision prediction speed is the same as that described in S203, which is the predicted vertical speed at the time of collision. The predicted contact position within the bus stop refers to the specific location within the bus stop where the abnormal vehicle is predicted to come into contact with the dangerous area. The indicator light refers to a lamp arranged along the length of the bus stop for issuing warning signals. Flashing red light means that the indicator light emits red light at a certain frequency to alert relevant personnel. For example, when the calculated vertical collision prediction speed when the abnormal vehicle comes into contact with the dangerous area is greater than 0, it indicates that there is a collision risk. The early warning device controls the indicator light at the predicted contact position within the bus stop to flash red to remind passengers on the platform and surrounding vehicles to pay attention to safety.

[0060] Specifically, when the warning device calculates that the vertical collision prediction velocity of the abnormal vehicle at the time of contact with the danger zone is greater than 0, indicating that the abnormal vehicle may collide with the danger zone, the warning device will control the indicator light at that location within the bus stop to flash red based on the predicted contact location. For example, after calculating that the vertical collision prediction velocity of an abnormal vehicle is 5m / s, which is greater than 0, indicating a collision risk, the warning device will immediately control the indicator light at the predicted contact location within the bus stop to flash red, alerting nearby personnel.

[0061] In some embodiments, the warning device can control the indicator light at the predicted contact location within the bus stop to flash red, and then continuously calculate the vertical collision prediction speed and predicted contact location when the abnormal vehicle contacts the danger zone. If the vertical collision prediction speed when the abnormal vehicle contacts the danger zone is less than or equal to 0, the warning device turns off the indicator light. If the vertical collision prediction speed is still greater than 0, the warning device continuously adjusts the area where the indicator light flashes red based on changes in the predicted contact location of the abnormal vehicle.

[0062] In other embodiments, the warning device can also mark the abnormal vehicle as a dangerous vehicle and send an alarm message to the surrounding warning devices after the abnormal vehicle avoids the dangerous area and leaves the monitoring area. The alarm information includes the license plate number of the dangerous vehicle, the vehicle type, the driving status table in the monitoring area and other information.

[0063] It is understandable that other methods can also be used to implement early warning operations for abnormal vehicles, which are not limited here.

[0064] The above embodiment enables waiting passengers at a bus stop to identify the source of danger if a vehicle deviates from its normal trajectory and collides with a bus stop due to operator error, mechanical failure, or sudden driver illness. However, the above embodiment cannot effectively determine whether a vehicle is an abnormal vehicle if it is traveling at high speed and has an abnormal trajectory. Furthermore, the fixed second preset duration set in the above embodiment does not take into account the actual urgency of the vehicle's collision. If a vehicle approaches a dangerous area at high speed, the fixed second preset waiting period may miss the opportunity for a warning.

[0065] See below Figure 3 , is another flow chart of a bus stop early warning method based on security monitoring in an embodiment of the present application; S301. The early warning device divides the bus stop area into a danger zone, a warning zone, and a driving zone based on the recognition of road markings by a surveillance camera.

[0066] Step S301 is similar to step S201 and will not be described again here.

[0067] S302: After a moving vehicle enters the driving area, the early warning device identifies the moving vehicle based on the monitoring video and constructs a driving status table for the moving vehicle.

[0068] Mobile vehicles are vehicles in motion on the road, as distinguished from stationary vehicles. The driving area is the driving area defined in S301. Surveillance video refers to the dynamic image data captured and transmitted in real time by surveillance cameras. The driving status table is a table that records driving parameters related to mobile vehicles, including position, heading, velocity, acceleration, and other data at different times after the mobile vehicle enters the monitoring area.

[0069] Specifically, when a moving vehicle enters the driving area, the early warning device first detects the moving vehicle through image recognition technology of the monitoring video, then assigns a unique identifier to the vehicle, and begins to collect the vehicle's driving data in real time, such as position, direction angle, speed, acceleration, etc., and then uses the Kalman filter algorithm to denoise the collected data and record the data in chronological order in the driving status table.

[0070] In some embodiments, it is also possible to detect vehicles entering the driving area through ground sensing coils installed in the driving area, trigger the early warning device to analyze the surveillance video, use license plate recognition technology to identify the moving vehicle, and then build a driving status table for the vehicle. At the same time, the speed and acceleration data of the moving vehicle are obtained through the radar sensor and entered into the driving status table of the moving vehicle.

[0071] It is understandable that other methods can also be used to construct a driving status table for a mobile vehicle, such as combining the communication between the on-board equipment and the early warning equipment to obtain the signal and driving status data of the vehicle entering the driving area, thereby constructing a driving status table, which is not limited here.

[0072] S303. When the direction angle of the moving vehicle changes from pointing outside the dangerous area to pointing into the dangerous area, the early warning device calculates the mean speed and acceleration standard deviation of the moving vehicle in the driving area within the first preset time period based on the driving status table.

[0073] Step S303 is similar to step S202 and will not be described again here.

[0074] S304. The early warning device determines whether the moving vehicle is in a situation where the average speed is greater than or equal to a preset speed threshold and the acceleration standard deviation is greater than or equal to a preset standard deviation threshold.

[0075] After the early warning device determines in step S304 that the moving vehicle is in a situation where the average speed is greater than or equal to the preset speed threshold and the acceleration standard deviation is greater than or equal to the preset standard deviation threshold, step S305 is executed. After the early warning device determines in step S304 that the moving vehicle is not in a situation where the average speed is greater than or equal to the preset speed threshold and the acceleration standard deviation is greater than or equal to the preset standard deviation threshold, step S306 is executed.

[0076] S305: The early warning device marks the moving vehicle as an abnormal vehicle.

[0077] Specifically, in step S304, after the warning device determines that the mean speed of the moving vehicle is greater than or equal to a preset speed threshold and the acceleration standard deviation is greater than or equal to a preset standard deviation threshold, the warning device marks the moving vehicle as an abnormal vehicle.

[0078] After the early warning device marks the moving vehicle as an abnormal vehicle in step S305, step S308 is executed.

[0079] S306. When the mean speed of the moving vehicle is greater than or equal to a preset speed threshold and the acceleration standard deviation is less than a preset standard deviation threshold, the early warning device determines the smoothness of the trajectory curve of the moving vehicle within the first preset time period based on the driving status table.

[0080] The trajectory smoothness is used to indicate the smoothness of the trajectory of a moving vehicle during driving, reflecting the stability of the vehicle. The higher the smoothness, the more stable the trajectory.

[0081] Specifically, when the mean speed of a moving vehicle is greater than or equal to a preset speed threshold and the standard deviation of its acceleration is less than a preset standard deviation threshold, the warning device extracts the vehicle's position data for a first preset time period from the driving status table to more comprehensively determine whether the vehicle is abnormal. The device then smoothes this position data using a spline interpolation algorithm to construct a continuous trajectory curve. The smoothness of the trajectory curve is then determined by calculating the rate of change of curvature. A smaller rate of change indicates a higher degree of smoothness.

[0082] In some embodiments, the position data can also be converted into two-dimensional plane coordinates, and the trajectory curve can be fitted using the least squares method. Then, the sum of the squares of the distances from the trajectory points to the fitting curve can be calculated. The smoothness of the trajectory curve can be measured by the size of the sum of the squares of the distances. The smaller the sum of the squares of the distances, the higher the smoothness.

[0083] It is understandable that other methods can also be used to determine the smoothness of the trajectory curve of the moving vehicle within the first preset time length, such as using Fourier transform to analyze the frequency components of the trajectory and judging the smoothness of the trajectory by the proportion of high-frequency components. This is not limited here.

[0084] S307: When the smoothness of the trajectory curve of the moving vehicle within the first preset time period is greater than or equal to a preset smoothness threshold, the early warning device marks the moving vehicle as an abnormal vehicle.

[0085] After the early warning device marks the moving vehicle as an abnormal vehicle in step S307, step S308 is executed.

[0086] S308. When the direction angle of the abnormal vehicle still points to the danger zone when it crosses the boundary of the warning area, the early warning device fits the position, speed, acceleration and distance from the danger zone of the abnormal vehicle within a third preset time period into a motion trajectory equation after the second preset time period.

[0087] Among them, abnormal vehicles are vehicles that are marked as potential safety hazards. The warning area boundary is the dividing line between the warning area and other areas. The second preset time length is a pre-set time interval for waiting so that the vehicle has enough driving distance. The third preset time length is determined by extending forward from the moment when the second preset time length ends. The motion trajectory equation is a mathematical equation that describes the motion trajectory of abnormal vehicles, which includes the relationship between parameters such as position, speed, and acceleration over time. For example, when an abnormal vehicle crosses the warning area boundary and the direction angle is still pointing to the dangerous area, the early warning device will fit the position, speed and other data of the vehicle within the third preset time length (such as 10 seconds) into a motion trajectory equation after the second preset time length (such as 2 seconds).

[0088] Specifically, when an abnormal vehicle crosses the boundary of the warning zone and its heading angle is still pointing toward the danger zone, the warning device first starts a timer and waits for a second preset duration. During this waiting period, it continues to collect data such as the vehicle's position, speed, acceleration, and distance from the danger zone. After the second preset duration expires, the warning device acquires all collected data from the vehicle within a third preset duration and then uses a data fitting algorithm to fit this data into a motion trajectory equation.

[0089] In some embodiments, after the second preset time period, before the warning device fits the position, speed, acceleration, and distance from the dangerous area of the abnormal vehicle within the third preset time period into a motion trajectory equation, a method for dynamically adjusting the second preset time period may be used: Specifically, if the abnormal vehicle's direction angle still points toward the danger zone when it crosses the warning zone boundary, the warning device calculates the abnormal vehicle's predicted vertical collision speed and predicted contact position when it contacts the danger zone based on the abnormal vehicle's motion trajectory equation within a fourth preset time period. The fourth preset time period is determined by extending forward from the moment the abnormal vehicle crossed the warning zone boundary. If the abnormal vehicle's predicted vertical collision speed within the fourth preset time period is greater than 0 and the density of waiting passengers at the predicted contact position is greater than or equal to a preset waiting passenger density threshold, the warning device calculates the abnormal vehicle's critical vertical collision time in the danger zone. The critical vertical collision time in the danger zone refers to the time required for the abnormal vehicle to reach a vertical distance from the danger zone boundary of 0. If the abnormal vehicle's critical vertical collision time in the danger zone is greater than the second preset time period, the warning device reduces the second preset time period to the fourth preset time period, replaces the second preset time period in step S308 with the fourth preset time period, and then executes step S308.

[0090] In other embodiments, before the warning device fits the position, speed, acceleration and distance from the dangerous area of the abnormal vehicle within the third preset time period into the motion trajectory equation after the second preset time period, it can also, when the vertical collision prediction speed of the abnormal vehicle within the fourth preset time period is greater than 0 and the density of waiting passengers at the contact prediction position is greater than or equal to the preset waiting passenger density threshold, if the vertical collision critical time of the abnormal vehicle in the dangerous area is less than or equal to the second preset time period and the vertical collision prediction speed of the abnormal vehicle is greater than 0, it means that the abnormal vehicle has a high vertical collision risk, and the number of waiting passengers at the current contact prediction position is greater than 0. Density. If the abnormal vehicle does not change its driving state, the waiting passengers at the predicted contact position will be at great risk of collision and unable to dodge in time. At this time, the early warning device controls the indicator light at the predicted contact position in the bus stop to flash orange and reminds the waiting passengers at the predicted contact position to leave the orange light area in advance through voice broadcast to reduce the density of waiting passengers at the predicted contact position. The early warning device continuously adjusts the indicator light flashing orange at the predicted contact position according to the changes in the driving state of the abnormal vehicle until the density of waiting passengers at the predicted contact position is less than the preset waiting passenger density threshold, then stops the indicator light flashing orange and continues to execute step S308.

[0091] It is understandable that other more accurate methods for determining the second preset duration may also be used, which are not limited here.

[0092] S309. The early warning device calculates the coordinates of the intersection of the abnormal vehicle and the boundary of the dangerous area based on the motion trajectory equation.

[0093] The intersection coordinates refer to the position of the intersection of the abnormal vehicle's motion trajectory and the boundary of the dangerous area in the three-dimensional coordinate system of the monitoring area.

[0094] Specifically, after obtaining the trajectory equation of the abnormal vehicle within the third preset time period, the warning device first needs to determine the boundary of the danger zone. It then solves the trajectory equation and the equation or geometric conditions of the danger zone boundary simultaneously to find the points where the two meet the intersection condition. These points are referred to as the intersection points. By calculating the coordinates of the intersection points, the specific location of the intersection between the abnormal vehicle's trajectory and the danger zone boundary is determined.

[0095] In some embodiments, the motion trajectory equation and the boundary of the dangerous area can also be visualized in a computer graphics coordinate system. Through a pixel-level collision detection algorithm, the pixel coordinates of the intersection of the trajectory curve and the boundary are found and then converted into actual geographic coordinates.

[0096] It is understandable that other methods can also be used to calculate the coordinates of the intersection of the abnormal vehicle and the boundary of the dangerous area, such as using a spatial geometry algorithm to calculate the geometric intersection of the motion trajectory and the boundary of the dangerous area, which is not limited here.

[0097] S310. The warning device calculates the vertical collision prediction speed and contact prediction position of the abnormal vehicle when it contacts the dangerous area based on the tangent vector of the trajectory equation at the intersection coordinates.

[0098] The tangent vector is the tangent direction vector of the trajectory equation at the intersection coordinates, representing the vehicle's direction of motion at that point. The vertical collision prediction velocity is the predicted collision velocity perpendicular to the boundary of the danger zone when the anomalous vehicle contacts the danger zone. The predicted contact position is the specific location where the anomalous vehicle is predicted to contact the danger zone, i.e., the intersection coordinates.

[0099] Specifically, the warning system first differentiates the trajectory equation to obtain the tangent vector at the intersection coordinates. This tangent vector represents the vehicle's direction and velocity at the intersection. It then determines the normal direction of the danger zone boundary and calculates the component of the tangent vector's projection onto the normal direction. This component represents the predicted vertical collision velocity. The predicted contact position is the intersection coordinates calculated previously.

[0100] It is understandable that other methods can also be used to calculate the vertical collision prediction speed and contact prediction position when the abnormal vehicle contacts the dangerous area, such as simulating the movement of the vehicle through a physics engine and calculating the vertical collision prediction speed and contact prediction position when the abnormal vehicle contacts the dangerous area. This is not limited here.

[0101] S311. When it is determined that the vertical collision prediction speed is greater than 0, the warning device controls the indicator light at the contact prediction position in the bus stop to flash red.

[0102] Step S311 is similar to step S204 and will not be described again here.

[0103] The embodiment of the present application can effectively identify a vehicle as abnormal when it is traveling at high speed and has an abnormal trajectory. Furthermore, when an abnormal vehicle may pose a danger to a high density of waiting passengers, the second preset duration is dynamically adjusted based on the vertical collision threshold time, making the warning time more reasonable. This ensures timely warnings while avoiding premature or late warnings, improving the effectiveness and relevance of warnings and better ensuring the safety of waiting passengers.

[0104] A bus stop warning method based on security monitoring in an embodiment of the present application is described above. The following introduces an exemplary warning device 100 provided in an embodiment of the present application.

[0105] Figure 4: is an exemplary hardware structure diagram of the early warning device 100 provided in an embodiment of the present application. In some embodiments, the early warning device 100 is a computer device, which includes a processor, a memory and a network interface connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The network interface of the computer device is used to communicate with other external terminals or servers through a network connection. In some embodiments, the network interface can be a wired network interface, and in some embodiments, the network interface can also be a wireless network interface. When the computer program is executed by the processor, a bus stop early warning method based on security monitoring in an embodiment of the present application is implemented.

[0106] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0107] In some embodiments of the present application, a computer-readable storage medium is also provided, comprising instructions. When the instructions are executed on the warning device 100, the warning device 100 can execute a bus stop warning method based on security monitoring in an embodiment of the present application.

[0108] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0109] As used in the above embodiments, the term “when” may be interpreted to mean “if” or “after” or “in response to determining that” or “in response to detecting that”, depending on the context. Similarly, the phrases “upon determining that” or “if (stated condition or event) is detected” may be interpreted to mean “if determining that” or “in response to determining that” or “upon detecting (stated condition or event)” or “in response to detecting (stated condition or event)”, depending on the context.

[0110] 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. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. 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) 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. The available medium can be a magnetic medium (e.g., a floppy disk, hard disk, tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive).

[0111] Those skilled in the art will appreciate that all or part of the process steps in the above-described method embodiments can be implemented by a computer program instructing the relevant hardware. The program can be stored in a computer-readable storage medium, and when executed, the program can include the process steps in the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A bus stop early warning method based on security monitoring, applied to early warning equipment, characterized in that: The method comprises: The warning device divides the bus stop area into a danger zone, a warning zone, and a travel zone based on the recognition of road markings by surveillance cameras. The danger zone is the area where the bus stop itself is located, the warning zone is the single lane area closest to the bus stop, and the travel zone is the other lane areas within the monitoring range that are not in the warning zone. The warning device marks as abnormal vehicles any moving vehicle whose average speed in the driving area is greater than or equal to a preset speed threshold and whose acceleration standard deviation is greater than or equal to a preset standard deviation threshold within a first preset time period, wherein the first preset time period is determined by extending forward and backward from the moment when the direction angle of the corresponding moving vehicle changes from pointing outside the danger zone to pointing inside the danger zone as the midpoint; When the abnormal vehicle crosses the boundary of the warning area and its direction angle is still pointing to the danger area, the warning device calculates, after a second preset time period, a vertical collision prediction speed and a contact prediction position of the abnormal vehicle when it contacts the danger area based on the current position, speed, acceleration of the abnormal vehicle and the distance from the danger area; When it is determined that the vertical collision prediction speed is greater than 0, the warning device controls the indicator light at the contact prediction position in the bus stop to flash red, and the indicator light is arranged along the length direction of the bus stop.

2. The method according to claim 1, characterized in that The early warning device marks as abnormal vehicles any moving vehicle whose average speed in the driving area within a first preset time period is greater than or equal to a preset speed threshold and whose acceleration standard deviation is greater than or equal to a preset standard deviation threshold. Specifically, the method includes: After a moving vehicle enters the driving area, the warning device identifies the moving vehicle based on the monitoring video and constructs a driving status table for the moving vehicle. The driving status table is the position, direction angle, speed, and acceleration of the moving vehicle at different times after entering the monitoring area. When the direction angle of the moving vehicle changes from pointing outside the danger zone to pointing into the danger zone, the warning device calculates the mean speed and the standard deviation of the acceleration of the moving vehicle in the driving zone within the first preset time period based on the driving state table; When the average speed of the moving vehicle in the driving area within the first preset time period is greater than or equal to a preset speed threshold and the acceleration standard deviation is greater than or equal to a preset standard deviation threshold, the early warning device marks the moving vehicle as an abnormal vehicle; When the average speed of the moving vehicle in the driving area within the first preset time period is less than a preset speed threshold and the acceleration standard deviation is less than a preset standard deviation threshold, the early warning device marks the moving vehicle as a normal vehicle.

3. The method according to claim 2, characterized in that Before the step of the early warning device marking the moving vehicle as a normal vehicle when the average speed of the moving vehicle in the driving area within the first preset time period is less than a preset speed threshold and the acceleration standard deviation is less than a preset standard deviation threshold, the method further includes: When the average speed of the moving vehicle in the driving area within the first preset time period is greater than or equal to a preset speed threshold and the acceleration standard deviation is less than a preset standard deviation threshold, the early warning device determines, based on the driving state table, a trajectory curve smoothness of the moving vehicle within the first preset time period, where the trajectory curve smoothness refers to the degree to which the driving trajectory of the moving vehicle within the first preset time period deviates from a straight line or a uniform curve; When the smoothness of the trajectory curve of the moving vehicle within the first preset time period is greater than or equal to a preset smoothness threshold, the early warning device marks the moving vehicle as an abnormal vehicle.

4. The method according to claim 1, wherein When the abnormal vehicle crosses the boundary of the warning area and its direction angle is still pointing to the danger area, the warning device calculates, after a second preset time period, based on the current position, speed, acceleration of the abnormal vehicle and the distance from the danger area, a vertical collision prediction speed and a contact prediction position when the abnormal vehicle contacts the danger area, specifically including: If the direction angle of the abnormal vehicle is still pointing to the danger zone when the abnormal vehicle crosses the boundary of the warning area, the early warning device fits the position, speed, acceleration and distance from the danger zone of the abnormal vehicle within a third preset time period into a motion trajectory equation after the second preset time period, and the third preset time period is determined by extending forward from the moment when the second preset time period ends; The early warning device calculates the coordinates of the intersection of the abnormal vehicle and the boundary of the dangerous area based on the motion trajectory equation; The warning device calculates a vertical collision prediction speed and a contact prediction position of the abnormal vehicle when it contacts the dangerous area based on a tangent vector of the trajectory equation at the intersection coordinates.

5. The method according to claim 4, characterized in that Before the step of fitting the position, speed, acceleration, and distance from the dangerous area of the abnormal vehicle within a third preset time period into a motion trajectory equation after the second preset time period, the method further includes: When the abnormal vehicle crosses the boundary of the warning area and its direction angle is still pointing to the danger area, the warning device calculates the vertical collision prediction speed and contact prediction position of the abnormal vehicle when it contacts the danger area based on the motion trajectory equation of the abnormal vehicle within a fourth preset time period, where the fourth preset time period is determined by extending forward from the moment when the abnormal vehicle crosses the boundary of the warning area; When the vertical collision prediction speed of the abnormal vehicle within a fourth preset time period is greater than 0 and the density of waiting passengers at the contact prediction position is greater than or equal to a preset waiting passenger density threshold, the early warning device calculates a critical vertical collision time of the abnormal vehicle in the danger zone, where the critical vertical collision time in the danger zone refers to the time required for the abnormal vehicle to reach a vertical distance of 0 from the boundary of the danger zone; When the critical time for vertical collision of the abnormal vehicle in the dangerous area is greater than the second preset time length, the warning device reduces the second preset time length to a fourth preset time length; When the critical vertical collision time of the abnormal vehicle in the dangerous area is less than or equal to the second preset time length, the early warning device controls the indicator light at the contact prediction position in the bus stop to flash red.

6. The method according to any one of claims 1 to 5, characterized in that The method further comprises: The warning device controls the indicator light at the predicted contact position in the bus stop to flash red and continuously calculates the vertical collision prediction speed and contact prediction position of the abnormal vehicle when it contacts the dangerous area; When the vertical collision prediction speed of the abnormal vehicle when it contacts the dangerous area is less than or equal to 0, the warning device turns off the indicator light; When the vertical collision prediction speed is still greater than 0, the warning device continuously adjusts the area where the indicator light flashes red according to the change of the contact prediction position of the abnormal vehicle.

7. The method according to claim 6, characterized in that After the step of the warning device continuously adjusting the area where the indicator light flashes red according to changes in the predicted contact position of the abnormal vehicle when the vertical collision predicted speed is still greater than 0, the method further includes: After the abnormal vehicle avoids the dangerous area and leaves the monitoring area, the early warning device marks the abnormal vehicle as a dangerous vehicle and sends an alarm message to the surrounding early warning devices. The alarm information includes the license plate number, vehicle type, driving status table in the monitoring area and other information of the dangerous vehicle.

8. An early warning device, characterized in that: The early warning device includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the early warning device to execute the method as described in any one of claims 1-7.

9. A computer program product comprising instructions, characterized in that When the computer program product is run on an early warning device, the early warning device is caused to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on the early warning device, the early warning device is caused to execute the method according to any one of claims 1 to 7.

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