Supervision method, system and device for highway traffic events and storage medium

Abstract

The invention relates to an expressway traffic incident supervision method, system and device and a storage medium, and belongs to the technical field of traffic supervision, and the method comprises the steps: carrying out the real-time monitoring based on a preset radar, and obtaining the traffic data of an expressway; analyzing the traffic data, and judging whether an abnormal event occurs or not; wherein the abnormal events at least comprise traffic accidents and traffic jams; if the abnormal event occurs, calling monitoring video data of the highway section where the abnormal event occurs, and generating and outputting alarm information with the monitoring video data and traffic data corresponding to the abnormal event; determining whether a dangerous vehicle exists based on the traffic data acquired in real time; and if the dangerous vehicle exists, determining an associated vehicle associated with the dangerous vehicle in real time, and sending warning information to a navigation platform which is in communication connection in advance. The method has the effects of improving the quick response and alarm of the abnormal event of the expressway and helping the expressway management personnel to process the abnormal event timely and efficiently.

Description

Technical Field

[0001] The present application relates to the technical field of traffic supervision, and in particular to a method, system, device and storage medium for supervising highway traffic incidents. Background Art

[0002] With the rapid development of my country's economy and society, the continuous growth of population and the gradual improvement of people's living standards, the number of motor vehicles in my country has reached an unprecedented scale and level, which has also led to the rapid development of highway-related businesses. While the expressway is developing rapidly, the number of road traffic incidents and the number of casualties are also increasing year by year.

[0003] Due to the characteristics of highways such as being closed, fast, and having large traffic volume, once a traffic incident or even a traffic accident occurs, it is very easy to cause a major and vicious road traffic accident with multiple casualties. Once an abnormal incident (such as a traffic accident) occurs, it is generally the drivers and passengers involved who call the police and rescue phone to inform the highway managers to arrive at the scene to deal with the abnormal incident. However, this operation can easily lead to a slowdown in road traffic and even delay the treatment of the drivers and passengers involved who have casualties due to the highway managers' untimely handling of abnormal incidents, so it needs to be improved. Summary of the invention

[0004] In order to improve the rapid response and warning to abnormal events on highways and help highway managers deal with abnormal events in a timely and efficient manner, the present application provides a method, system, device and storage medium for supervising highway traffic events.

[0005] In the first aspect, the present application provides a method for supervising highway traffic incidents, which adopts the following technical solutions: Based on the preset radar, real-time monitoring and acquisition of highway traffic data; Analyze the traffic data and determine whether an abnormal event occurs; wherein the abnormal event at least includes a traffic accident and a traffic jam; If an abnormal event occurs, the monitoring video data of the highway section where the abnormal event occurs is retrieved, and an alarm message containing the monitoring video data and the traffic data corresponding to the abnormal event is generated and output, so that the road management personnel are informed of the alarm message; Based on the traffic data acquired in real time, determine whether there is a dangerous vehicle; wherein the dangerous behavior of the dangerous vehicle includes pre-dangerous behavior and / or post-interference behavior; Predicting the driving trend and estimated driving behavior of each vehicle based on the current driving behavior of the vehicle, determining the feasibility of the estimated driving behavior, and if not feasible, determining the vehicle as a dangerous vehicle; If there is a dangerous vehicle, determine the associated vehicles related to the dangerous vehicle in real time; analyze the dangerous behavior of the dangerous vehicle and the driving behavior of the corresponding target vehicle, and filter out the associated vehicles whose corresponding driving behavior does not conflict with the dangerous behavior of the dangerous vehicle from the target vehicles; If there is a vehicle with a directional driving habit among the dangerous vehicle and the corresponding associated vehicles, the corresponding directional driving area is determined, and disturbed vehicles that are easily disturbed by the directional driving habit are screened out, wherein the disturbed vehicles at least include vehicles whose current driving routes intersect with the directional driving area and vehicles that have driving blind spots due to the dangerous vehicle moving into the directional driving area; the disturbed vehicles and the associated vehicles are combined as the associated vehicles of the dangerous vehicle; Generate warning information with a danger zone for each associated vehicle, predict an adjustment behavior of the associated vehicle based on the danger zone of the associated vehicle, and generate a buffer zone based on the adjustment behavior if the adjustment behavior meets a preset adjustment condition; The dangerous area and the buffer area are merged to generate warning information, and the vehicle navigation of the vehicle is controlled to display the corresponding warning information; if there are multiple overlapping dangerous areas and they belong to the same associated vehicle, the associated vehicle is determined as a dangerous vehicle; Whenever an abnormal event occurs, the severity of the abnormal event is evaluated, and the scope of the abnormal event is determined based on the severity, wherein the scope of the abnormal event at least includes the affected lanes and the affected vehicles; Determine the degree of impact of each affected vehicle in real time, and based on the degree of impact, select the evading vehicles that meet the avoidance conditions from the affected vehicles, and the avoidance period during which each of the evading vehicles meets the avoidance conditions; wherein the avoidance conditions are: based on the lane length occupied by the target affected vehicle when changing lanes in the historical period, determine whether there is an actual spacing greater than the lane length on the evaluation lane currently parallel to the affected lane where the target affected vehicle is located, if so, it is considered that the target affected vehicle meets the avoidance conditions; A reminder message with an avoidance period and an avoidance plan is sent to the avoidance vehicle to remind the avoidance vehicle to avoid the affected lane within the avoidance period.

[0006] By adopting the above technical solution, traffic data is obtained by monitoring with the help of radars preset on highways, wherein the traffic data is used to reflect the traffic conditions on the highway, such as vehicle driving conditions, traffic flow conditions and vehicle distances, etc. Then, based on the traffic data, it is automatically analyzed whether there is an abnormal event. If so, it will immediately trigger the generation of an alarm message for road management personnel to be informed. In addition, the monitoring video of the highway section where the abnormal time occurred will be added to the alarm message, so that the road management personnel can know the severity of the abnormal event in a more detailed and vivid way in the form of video, and then make subsequent response actions. ; In addition, dangerous vehicles can be considered as vehicles that may cause abnormal events, such as vehicles that travel at high speeds and frequently change lanes, and related vehicles can be considered as vehicles that are susceptible to the influence of dangerous vehicles and directly or indirectly cause abnormal events. If there are dangerous vehicles, this application proposes to find out the related vehicles that are susceptible to their adverse effects, and use the pre-communicated navigation platform to send warning information to the related vehicles, so that the related vehicles can clearly and visually know their positional relationship and distance information with the dangerous vehicles on the navigation path, so as to help the related vehicles effectively avoid and stay away from dangerous vehicles, thereby indirectly reducing the probability of abnormal events. In summary, this application uses radar monitoring assisted video evidence collection to realize the monitoring of abnormal events on the highway, so as to improve the timely response speed of highway management personnel to abnormal events.

[0007] Optionally, the traffic data at least includes vehicle driving data. The traffic data at least includes vehicle driving data, and the real-time determination of the associated vehicle associated with the dangerous vehicle includes: Based on the location of the dangerous vehicle, retrieve pre-screened vehicles whose navigation routes overlap with the navigation route of the dangerous vehicle from a preset navigation platform; Based on the current vehicle speed of each pre-screened vehicle, the current vehicle speed of the dangerous vehicle, and the travel distance between the pre-screened vehicle and the dangerous vehicle, associated vehicles are screened out from the pre-screened vehicles; wherein the associated vehicles satisfy: the associated vehicles can travel to a specified range around the dangerous vehicle on a corresponding section of the road where there is an overlapping route with the dangerous vehicle.

[0008] By adopting the above technical solution, the solution further limits the judgment logic of related vehicles, and the solution not only simply considers the vehicles on the road section where the dangerous vehicle is currently located, but also considers the road structure where different forks merge or diverge in the highway, and includes vehicles from different sections that are easily affected by dangerous vehicles in the consideration range, so as to improve the avoidance effect of abnormal events and reduce the probability of abnormal events. Specifically, firstly, pre-screened vehicles that will have overlapping routes with dangerous vehicles are screened out, and then based on the speed of each pre-screened route and the travel distance with the dangerous vehicle, it is judged whether the pre-screened vehicle can approach the dangerous vehicle on the corresponding section of the overlapping route, that is, drive to the specified range around the dangerous vehicle. If it can, then the pre-screened vehicle is an associated vehicle, which is easily affected by the dangerous vehicle and directly or indirectly causes abnormal events.

[0009] Optionally, the method further includes: Whenever an abnormal event occurs, the severity of the abnormal event is evaluated, and the scope of the abnormal event is determined based on the severity, wherein the scope of the abnormal event at least includes the affected lanes and the affected vehicles; Determine the degree of impact of each affected vehicle in real time, and based on the degree of impact, select avoidance vehicles that meet avoidance conditions from the affected vehicles, and avoidance time periods during which each avoidance vehicle meets the avoidance conditions; A reminder message with an avoidance period and an avoidance plan is sent to the avoidance vehicle to remind the avoidance vehicle to avoid the affected lane within the avoidance period.

[0010] By adopting the above technical solution, in order to reduce the occurrence of abnormal events, the degree of impact of subsequent vehicles (i.e., affected vehicles) passing through the section where the abnormal event is located is analyzed, and the degree of impact of each affected vehicle is analyzed, and the avoiding vehicles are screened out, and the avoidance time period of the specified avoidance plan is determined for the avoiding vehicles, so that the avoiding lane can smoothly avoid the affected lane and reduce the degree of impact of the abnormal event, thereby indirectly helping road management personnel to improve the efficiency of maintenance and processing of abnormal events.

[0011] Optionally, the method further includes: Based on the traffic data of each preset road section obtained in real time, determine the risk factor of vehicles in each preset road section, obtain the current environmental data of each preset road section, and the abnormal event history record of each preset road section, and use the pre-built prediction model to predict the probability of abnormal events in each preset road section in real time; When the probability of occurrence of an abnormal event corresponding to a first preset road section is higher than a preset probability, a warning message is generated and outputted so that the driver and passengers corresponding to the vehicle on the first preset road section can be informed of the warning message.

[0012] By adopting the above-mentioned technical scheme, in addition to using radar data to monitor real-time traffic data and determine whether an abnormal event has occurred at present, the present application also proposes to use a prediction model to predict the probability of abnormal events occurring on each preset road section, and comprehensively considers the vehicle risk factor, environmental data and the historical records of abnormal events on each preset road section, that is, a comprehensive prediction is made from multiple aspects such as the influence of the vehicle itself, the geographical location of the road itself, and the natural environment, and when the predicted probability of abnormal events is high (that is, higher than the preset probability), an early warning is issued to the drivers and passengers of the corresponding preset road section, so as to effectively avoid the occurrence of abnormal events.

[0013] Optionally, the method further includes: When an abnormal event occurs, obtaining vehicle travel data of vehicles involved in the abnormal event during a specified period before and when the abnormal event occurs from traffic data obtained in real time; Based on the vehicle driving data and the monitoring video data corresponding to the abnormal event, a simulation animation is generated and output, wherein the simulation animation is used to display the vehicle status of the vehicle involved before and after the abnormal event in an animated form, and the vehicle status includes at least the vehicle position.

[0014] By adopting the above-mentioned technical scheme, since the monitoring video data retrieved after determining the abnormal event has a delay, and since the vehicles on the highway have a high speed, the monitoring video is not easy to clearly and specifically record the vehicle status of the vehicle involved before and after the abnormal event occurs. Therefore, the present application generates an animation based on the vehicle driving data. The animation can be considered to be used to display the vehicle driving path of the vehicle involved in the entire process before and after the abnormal event occurs, so as to assist road management personnel to more clearly understand the entire process of the abnormal event and help road management personnel to determine the responsibility of the vehicle involved.

[0015] Optionally, if the abnormal event is a traffic accident, the vehicle state also includes vehicle deformation; The generating and outputting a simulation animation based on the vehicle driving data and the monitoring video data corresponding to the abnormal event includes: Based on the vehicle driving data and the surveillance video data corresponding to the abnormal event, determine the vehicle position information of the vehicle involved at each moment in a specified time period before the abnormal event occurs, and generate a simulation animation for displaying the vehicle driving process; If the abnormal event is a traffic accident, the deformation of the impacted position of the vehicle involved is determined by a preset simulation model based on the vehicle speed of the vehicle involved when the abnormal event occurs and the impacted position of the vehicle involved, and the deformation of the impacted position is displayed in the simulation animation.

[0016] By adopting the above technical solution, if the abnormal event is a traffic accident, that is, the vehicle involved is hit, it can be a collision between multiple vehicles involved, or it can be a collision between the vehicle involved and an obstacle or other infrastructure. In this case, the application will perform a collision simulation on the vehicle involved corresponding to such abnormal event, and use the simulation model to determine the deformation of the impact position. The deformation can be reflected in the form of data so that road management personnel can know the severity of the abnormal event in a more concrete way.

[0017] Optionally, each of the preset road sections is pre-divided into a number of unit road sections; The method further comprises: At every designated period, determining a vehicle travel path of vehicles passing through each preset road section within the designated period; For each preset road section, the unit road sections in each preset road section that overlap with the vehicle driving path and the corresponding number of overlaps are determined, and based on the number of overlaps, the road section maintenance plan for each preset road section is determined.

[0018] By adopting the above technical solution, the present application provides a new determination scheme for determining whether a highway section needs maintenance, that is, making full use of the traffic data obtained by radar monitoring to generate a vehicle driving path, and then determining whether maintenance is needed based on the number of times the vehicle driving path overlaps with the specific lane position in the preset section.

[0019] In a second aspect, the present application provides a highway traffic incident supervision system, comprising: Traffic data monitoring module, used to monitor and obtain highway traffic data in real time based on preset radar; An abnormal event analysis module, used to analyze the traffic data and determine whether an abnormal event occurs; wherein the abnormal event at least includes a traffic accident and a traffic jam; An abnormal event alarm module is used to retrieve the monitoring video data of the highway section where the abnormal event occurred, generate and output an alarm message containing the monitoring video data and the traffic data corresponding to the abnormal event, so that the road management personnel can be informed of the alarm message; An abnormal event warning module is used to determine whether there is a dangerous vehicle based on the traffic data obtained in real time; wherein the dangerous behavior of the dangerous vehicle includes pre-dangerous behavior and / or post-interference behavior; Predicting the driving trend and estimated driving behavior of each vehicle based on the current driving behavior of the vehicle, determining the feasibility of the estimated driving behavior, and if not feasible, determining the vehicle as a dangerous vehicle; If there is a dangerous vehicle, determine the associated vehicles related to the dangerous vehicle in real time; analyze the dangerous behavior of the dangerous vehicle and the driving behavior of the corresponding target vehicle, and filter out the associated vehicles whose corresponding driving behavior does not conflict with the dangerous behavior of the dangerous vehicle from the target vehicles; If there is a vehicle with a directional driving habit among the dangerous vehicle and the corresponding associated vehicles, the corresponding directional driving area is determined, and disturbed vehicles that are easily disturbed by the directional driving habit are screened out, wherein the disturbed vehicles at least include vehicles whose current driving routes intersect with the directional driving area and vehicles that have driving blind spots due to the dangerous vehicle moving into the directional driving area; the disturbed vehicles and the associated vehicles are combined as the associated vehicles of the dangerous vehicle; Generate warning information with a danger zone for each associated vehicle, predict an adjustment behavior of the associated vehicle based on the danger zone of the associated vehicle, and generate a buffer zone based on the adjustment behavior if the adjustment behavior meets a preset adjustment condition; The dangerous area and the buffer area are merged to generate warning information, and the vehicle navigation of the vehicle is controlled to display the corresponding warning information; if there are multiple overlapping dangerous areas and they belong to the same associated vehicle, the associated vehicle is determined as a dangerous vehicle; A vehicle impact avoidance module, used for evaluating the severity of an abnormal event whenever an abnormal event occurs, and determining the impact range of the abnormal event based on the severity, wherein the impact range at least includes the impact lanes and the impact vehicles; Determine the degree of impact of each affected vehicle in real time, and based on the degree of impact, select the evading vehicles that meet the avoidance conditions from the affected vehicles, and the avoidance period during which each of the evading vehicles meets the avoidance conditions; wherein the avoidance conditions are: based on the lane length occupied by the target affected vehicle when changing lanes in the historical period, determine whether there is an actual spacing greater than the lane length on the evaluation lane currently parallel to the affected lane where the target affected vehicle is located, if so, it is considered that the target affected vehicle meets the avoidance conditions; A reminder message with an avoidance period and an avoidance plan is sent to the avoidance vehicle to remind the avoidance vehicle to avoid the affected lane within the avoidance period.

[0020] In a third aspect, the present application provides a highway traffic incident monitoring device, characterized in that it includes a memory and a processor, and the memory stores a computer program that can be loaded by the processor and execute any one of the methods described in the first aspect.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and execute any one of the methods described in the first aspect.

[0022] In summary, this application includes the following beneficial technical effects: This application integrates existing radar and surveillance video resources to achieve radar all-weather event detection and monitoring, and surveillance video to assist in evidence collection and accountability, providing support for the intelligent goal of "measurable, visible, and serviceable" highway management; monitoring data and video surveillance data are connected to the highway integrated management platform to break through operational monitoring information islands and data barriers, realize comprehensive presentation of multi-source information, improve information utilization efficiency, and enhance the work efficiency of managers. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 It is a flow chart of a method for supervising highway traffic incidents disclosed in an embodiment of the present application.

[0025] Figure 2 It is a logic flow chart for determining whether there is an abnormal event of traffic congestion in an embodiment of the present application.

[0026] Figure 3 It is a structural block diagram of a highway traffic incident supervision system disclosed in an embodiment of the present application.

[0027] Explanation of the accompanying drawings: 1. Traffic data monitoring module; 2. Abnormal event analysis module; 3. Abnormal event alarm module; 4. Abnormal event early warning module. DETAILED DESCRIPTION

[0028] The following is combined with Figure 1-3 This application is described in further detail.

[0029] The embodiment of the present application discloses a method for supervising highway traffic incidents. The method for supervising highway traffic incidents (hereinafter referred to as the supervision method) is specifically used to monitor the driving conditions of vehicles on the highway, and analyze whether abnormal events occur based on the monitoring results. Abnormal events specifically include traffic accidents, traffic jams, etc., and when an abnormal event occurs, it is also used to retrieve the monitoring video of the preset road section where the abnormal event occurs, and finally generate and output alarm information with monitoring data and monitoring video related to the abnormal event, so that road management personnel can be informed of the alarm information, and use it as evidence to efficiently implement the handling plan for abnormal events. The executor of the supervision method of the present application is the supervision system for highway traffic incidents (hereinafter referred to as the supervision system), which will be discussed in conjunction with the attached Figure 1 The specific process steps of the supervision method are elaborated in detail.

[0030] S101, based on the preset radar, monitors and obtains the traffic data of the highway in real time.

[0031] In implementation, the expressway is divided into several preset sections in advance, and each preset section is equipped with several radar monitoring modules along its length, and the radar monitoring modules are used to monitor the traffic data of the preset section. The traffic data specifically includes the vehicle driving data corresponding to the preset section, and the vehicle driving data specifically includes the basic information of the vehicle, the vehicle speed, and the vehicle location information; the basic information of the vehicle specifically includes the license plate number, and the basic information of the vehicle is obtained by taking pictures of the camera installed in combination with the radar.

[0032] S102, analyzing the traffic data and determining whether an abnormal event occurs; wherein the abnormal event at least includes a traffic accident and a traffic jam.

[0033] In practice, all radar monitoring modules are connected to the supervision system, which pre-stores the correspondence between the communication address of each radar monitoring module, the actual geographical location information, and the corresponding preset road section number. The supervision system is used to obtain traffic data of all preset road sections and analyze the traffic data to determine whether there are any abnormal events.

[0034] Specifically, the analysis method for abnormal events of traffic congestion is as follows: Based on the traffic data acquired in real time, the supervision system is used to determine whether there is a vehicle whose vehicle speed is lower than the preset speed (hereinafter referred to as the first vehicle), and if it is determined whether there are other first vehicles before and after the first vehicle, the queue length L of the first vehicles is determined until there is no first vehicle, and the time when the vehicle speed of the first vehicle remains in the state of being lower than the preset speed is taken as the congestion duration T, and the time when the vehicle speed of the first vehicle remains in the state of being not lower than the preset speed after switching from the state of being lower than the preset speed to the state of being not lower than the preset speed is taken as the interruption duration t; After confirming the completion of the above data, execute Figure 2 The logical steps are as follows: first determine the relationship between L and the preset congestion length thresholds a, b, c, and then determine the relationship between T and the congestion duration thresholds m, t, and the congestion interruption threshold n; if the result of the judgment is light congestion, moderate congestion, or severe congestion, it is considered that an abnormal event exists, and the abnormal event is specifically a traffic jam; otherwise, if the judgment result is unimpeded or basically unimpeded, there is no abnormal event of traffic jam. It should be noted that when executing Figure 2When the logic step shown is completed, the supervision system will update L, T, and t in real time; once any value of L, T, and t changes, the current logic step will be interrupted and re-executed. Figure 2 The logical steps described.

[0035] Specifically, the embodiment of the present application exemplarily provides the following analysis method for determining whether an abnormal event is a traffic accident: Based on the traffic data acquired in real time, the supervision system determines whether there is a second vehicle with a vehicle speed of 0. If so, it determines whether the duration T' when the speed of the second vehicle continues to be 0 exceeds the duration threshold m'. If so, it determines whether there are multiple second vehicles. If so, based on the position information of the second vehicle, it determines whether the distance between adjacent second vehicles is not greater than 0. If so, an abnormal event has occurred, and it is a traffic accident. If there are not multiple second vehicles, based on the position information of the second vehicle, it determines the distance between the second vehicle and the infrastructure of the preset road section (such as roadside guardrails). If the distance is not greater than 0, an abnormal event has occurred, and it is a traffic accident.

[0036] S103, if an abnormal event occurs, the monitoring video data of the preset road section where the abnormal event occurs is retrieved, and an alarm message containing the monitoring video data and the traffic data corresponding to the abnormal event is generated and output, so that the road management personnel are informed of the alarm message.

[0037] In practice, if an abnormal event occurs, the supervision system will determine the preset road section where the abnormal event occurs (hereinafter referred to as the first preset road section) based on the location information of the vehicle corresponding to the abnormal event (i.e., the vehicle involved). Correspondingly, if the abnormal event is a traffic jam, the monitoring video data of the preset road section where all the first vehicles corresponding to the abnormal event are located will be retrieved; if the abnormal event is a traffic accident, the monitoring video data of the preset road section where all the second vehicles corresponding to the abnormal event are located will be retrieved. Finally, the supervision system generates an alarm message with traffic data and monitoring video data related to the abnormal event, and then informs the road management personnel of the alarm message by displaying it on the preset system main page, or sending the alarm message to the mobile terminal of the road management personnel.

[0038] In addition, in other embodiments, the supervision system may be pre-communicated with a navigation platform (such as the AutoNavi map navigation platform), and the supervision system is used to generate reminder information about the preset section where the abnormal event in the alarm information is located, as well as the specific type of the abnormal event (such as traffic congestion and traffic accidents), and send the reminder information to the navigation platform, so that the navigation platform broadcasts the reminder information to all drivers and passengers on the preset section of the navigation route where the abnormal event occurs, so that the corresponding drivers and passengers can be informed of the reminder information when logging into the navigation platform and navigating.

[0039] S104, based on the traffic data acquired in real time, determining whether there is a dangerous vehicle; wherein the dangerous behavior of the dangerous vehicle includes pre-dangerous behavior and / or post-interference behavior; Predicting the driving trend and estimated driving behavior of each vehicle based on the current driving behavior of the vehicle, determining the feasibility of the estimated driving behavior, and if not feasible, determining the vehicle as a dangerous vehicle; If there is a dangerous vehicle, determine the associated vehicles related to the dangerous vehicle in real time; analyze the dangerous behavior of the dangerous vehicle and the driving behavior of the corresponding target vehicle, and filter out the associated vehicles whose corresponding driving behavior does not conflict with the dangerous behavior of the dangerous vehicle from the target vehicles; If there is a vehicle with a directional driving habit among the dangerous vehicle and the corresponding associated vehicles, the corresponding directional driving area is determined, and disturbed vehicles that are easily disturbed by the directional driving habit are screened out, wherein the disturbed vehicles at least include vehicles whose current driving routes intersect with the directional driving area and vehicles that have driving blind spots due to the dangerous vehicle moving into the directional driving area; the disturbed vehicles and the associated vehicles are combined as the associated vehicles of the dangerous vehicle; Generate warning information with a danger zone for each associated vehicle, predict an adjustment behavior of the associated vehicle based on the danger zone of the associated vehicle, and generate a buffer zone based on the adjustment behavior if the adjustment behavior meets a preset adjustment condition; The dangerous area and the buffer area are merged to generate warning information, and the vehicle navigation of the vehicle is controlled to display the corresponding warning information; if there are multiple overlapping dangerous areas and they belong to the same associated vehicle, the associated vehicle is determined as a dangerous vehicle.

[0040] The “determining in real time the associated vehicles associated with the dangerous vehicle” in S104 includes: Based on the location of the dangerous vehicle, retrieve pre-screened vehicles whose navigation routes overlap with the navigation route of the dangerous vehicle from a preset navigation platform; Based on the current vehicle speed of each pre-screened vehicle, the current vehicle speed of the dangerous vehicle, and the travel distance between the pre-screened vehicle and the dangerous vehicle, associated vehicles are screened out from the pre-screened vehicles; wherein the associated vehicles satisfy: the associated vehicles can travel to a specified range around the dangerous vehicle on a corresponding road section where there is an overlapping route with the dangerous vehicle.

[0041] In implementation, the risk coefficient of each vehicle is comprehensively derived based on the vehicle position information and vehicle speed in the vehicle driving data. Exemplarily, the risk coefficient calculation method disclosed in the embodiment of the present application is: determine the frequency of the corresponding vehicle changing lanes according to the vehicle position information, and the frequency can be expressed as the time interval between two adjacent lane changes, and then determine the first risk value of the frequency corresponding to each vehicle position information according to the different frequency ranges stored in the preset first correspondence table and the first risk value corresponding to each frequency range; then determine the speed difference between the vehicle speed and the speed upper limit set for the preset road section, and determine the second risk value corresponding to each vehicle speed according to the different speed difference ranges stored in the preset second correspondence table and the second risk value corresponding to each speed difference range; risk coefficient = first risk value + second risk value.

[0042] The supervision system is used to mark vehicles with a risk factor higher than the risk threshold as dangerous vehicles; in addition, the present application will also predict the driving trend of the vehicle based on the current driving behavior of the vehicle. For example, if the current speed of the vehicle decreases or increases compared to the speed at the previous moment, and the difference is higher than the preset difference, the vehicle is considered to have a trend of speeding up or slowing down, and accordingly there is a speeding up or slowing down behavior (i.e., the estimated driving behavior); or if the current vehicle position is gradually approaching the dividing line of the adjacent lane compared to the vehicle position at the previous moment, the vehicle is considered to have a lane changing trend and a corresponding lane changing behavior (i.e., the estimated driving behavior). At this time, it is analyzed whether the estimated driving behavior of the vehicle is feasible, that is, it is analyzed whether the vehicles before and after the vehicle and the adjacent lanes have the conditions for the vehicle to perform the aforementioned estimated formal behavior. If the formal behavior of the vehicle intersects with the driving paths of the vehicles around it, it is considered to be infeasible, and the vehicle can also be considered to be a dangerous vehicle.

[0043] The supervision system is pre-communicated with the navigation platform, and the supervision system can display the preset road section where the abnormal event in the warning information is located, as well as the specific type of abnormal event (such as traffic congestion and traffic accidents) on the navigation interface of the vehicle's on-board terminal through the navigation platform. In addition, if there is a dangerous vehicle, the supervision system will send a query application to the navigation platform, and the query application includes the current vehicle location information of the dangerous vehicle, so that when the navigation platform receives the query application, it will first query the navigation route of the dangerous vehicle (hereinafter referred to as Route A). If the dangerous vehicle has not logged into the navigation platform and navigated, the navigation platform will determine the road section where the dangerous vehicle is located based on the vehicle location information of the dangerous vehicle; and then determine the navigation route that the dangerous vehicle may travel in the future based on the road section (hereinafter referred to as Route B). Route B refers to all navigation routes in the map that include the road section where the dangerous vehicle is currently located.

[0044] The navigation platform is then used to query the pre-screened vehicles. The route A or route B of the pre-screened vehicles overlaps with the navigation route of the dangerous vehicle (i.e., overlapping routes). The supervision system is used to receive the pre-screened routes obtained by the navigation platform, and based on the vehicle position information of the pre-screened routes, determine the current section of the road where the pre-screened vehicles are located and the current vehicle speed, and then determine the travel distance between each pre-screened route and the dangerous vehicle, and determine whether each pre-screened route can be moved to the specified range around the dangerous vehicle on the corresponding section of the road where there is an overlapping route with the dangerous vehicle based on the current vehicle speed and the travel distance between the remaining dangerous vehicles. Exemplarily, the range of a specified radius in the preset section where the dangerous vehicle is located and centered on the dangerous vehicle can be used as the specified range around the dangerous vehicle.

[0045] After the associated vehicle is found, the associated vehicle and the dangerous vehicle are analyzed to see whether they have a habit of directional driving. The directional driving can be understood as the vehicle is not centered in the lane it is in, but is biased to one side of the lane, and in the historical period, one side of the vehicle will also occupy the adjacent lane. If the above-mentioned directional driving habit exists, all associated vehicles and pre-screened vehicles will be screened for disturbed vehicles, and the disturbed vehicle will also be used as an associated vehicle of the dangerous vehicle, that is, the disturbed vehicle and the associated vehicle are taken as a union. Then, based on the current azimuth relationship between each associated vehicle and the corresponding dangerous vehicle, the distance between the vehicles and the current driving speed of the associated vehicle, a dangerous area is generated. The dangerous area refers to the area where the occupied area corresponding to the dangerous vehicle when the dangerous vehicle performs a dangerous behavior at time A intersects with the driving area of ​​the associated vehicle at time A, and the associated vehicle cannot avoid it. The dangerous area is the intersection area; the buffer area can refer to an area located outside the dangerous area, which can be used by the associated vehicle to avoid the aforementioned dangerous area by adjusting behaviors such as deceleration or changing lanes. Finally, warning information will be generated for each associated vehicle, which will at least include the dangerous area and the buffer area formed when the adjustment conditions are met. Finally, the corresponding warning information will be displayed in the vehicle navigation interface of the associated vehicle through the navigation platform.

[0046] Optionally, the supervision method further comprises the following steps: S105, based on the traffic data of each preset road section obtained in real time, determining the risk factor of vehicles in each preset road section, obtaining the current environmental data of each preset road section, and the abnormal event history record of each preset road section, and predicting the probability of abnormal event occurrence of each preset road section in real time through a pre-built prediction model; S106, when the probability of occurrence of an abnormal event corresponding to the first preset road section is higher than the preset probability, generate and output warning information so that the driver and passengers corresponding to the vehicle on the first preset road section can be informed of the warning information.

[0047] In implementation, the environmental data may specifically be visibility data and rainfall amount corresponding to the preset road section; the supervision system is also used to retrieve the historical records of abnormal events in the preset road section within a specified time period before the current time to determine the number of abnormal events that occurred in the preset road section. The supervision system inputs the environmental data, the number of abnormal events, and the risk factor of all vehicles into the pre-built prediction model, which is used to sum all the aforementioned data to obtain a score, and based on several score ranges stored in the preset third correspondence table and the probability value corresponding to each score range, determine the probability value corresponding to the score, and use the probability value as the probability of abnormal event occurrence.

[0048] The first preset road section refers to a preset road section where the probability of an abnormal event occurring is higher than the preset probability. If the first preset road section exists, a warning message is sent to the drivers and passengers on the first preset road section to remind the corresponding drivers and passengers to pay attention to driving safety. The method of informing the drivers and passengers of the warning message can be as described above, using the navigation platform to broadcast the warning message during the navigation process for the drivers and passengers.

[0049] Optionally, the supervision method further comprises the following steps: S107, when there is an abnormal event, obtaining vehicle travel data of vehicles involved in the abnormal event within a specified time period before and when the abnormal event occurs from the traffic data obtained in real time; S108, generating and outputting a simulation animation based on the vehicle driving data and the monitoring video data corresponding to the abnormal event, the simulation animation is used to display the vehicle state of the vehicle involved before and after the abnormal event in an animation form, and the vehicle state includes at least the vehicle position; If the abnormal event is a traffic accident, the vehicle state also includes the vehicle deformation; S107 specifically includes the following steps: Based on the vehicle driving data and the surveillance video data corresponding to the abnormal time, the vehicle position information of the vehicle involved at each moment in the specified time period before the abnormal event occurs is determined, and a simulation animation for displaying the vehicle driving process is generated; If the abnormal event is a traffic accident, the deformation of the impact position of the vehicle involved is determined through a preset simulation model based on the vehicle speed of the vehicle involved when the abnormal event occurs and the impact position of the vehicle involved, and the deformation of the impact position is displayed in the simulation animation.

[0050] In implementation, whenever an abnormal event occurs, the supervision system is used to extract all traffic data during the specified time period before and during the abnormal event, and according to the vehicle position information and vehicle speed at each acquisition moment in the specified time period, as well as the pre-built vehicle three-dimensional model and the preset road section three-dimensional model, set the initial position of the vehicle three-dimensional model in the preset road section three-dimensional model, and then according to the preset conversion rules, convert the vehicle speed and vehicle position information at each acquisition moment in the specified time period to determine the position of the vehicle model in the preset road section three-dimensional model at each acquisition moment, and finally generate a simulation animation according to the position of the vehicle model in the preset road section in the three-dimensional model at all acquisition moments. Among them, the preset conversion rule is to convert the actual moving path of the vehicle in the preset road section at adjacent acquisition moments into the moving path of the vehicle three-dimensional model in the preset road section three-dimensional model. Thus, the simulated animation driving auxiliary monitoring video data can help road management personnel to know the whole process of abnormal events more specifically and clearly.

[0051] If the abnormal event is a traffic accident, the deformation of the impacted position of the vehicle involved in the accident is simulated based on the vehicle speed and impacted position corresponding to the acquisition time when the abnormal event occurred, and the preset simulation model (such as ANSYS collision simulation software). The deformation can be specifically reflected in the form of stress data, and the corresponding deformation is displayed in the last frame of the simulation animation. This allows road management personnel to know the severity of the abnormal event based on the simulation results (i.e., deformation).

[0052] Optionally, the regulatory approach also includes: Whenever an abnormal event occurs, the severity of the abnormal event is evaluated, and the scope of the abnormal event is determined based on the severity, wherein the scope of the abnormal event at least includes the affected lanes and the affected vehicles; Determine the degree of impact of each affected vehicle in real time, and based on the degree of impact, select the avoidance vehicles that meet the avoidance conditions from the affected vehicles, as well as the avoidance time period during which each avoidance vehicle meets the avoidance conditions; A reminder message with an avoidance period and an avoidance plan is sent to the avoidance vehicle to remind the avoidance vehicle to avoid the affected lane within the avoidance period.

[0053] During implementation, whenever an abnormal event occurs, the scope of the abnormal event can be determined based on the severity of the abnormal event. The severity here can be considered as the time required for the abnormal event to be completely resolved, and the factors to be considered for the required time may at least include: the time required for the road management department to travel to the point where the abnormal event occurred, and the road area occupied by the abnormal event; the supervision system pre-stores the correspondence between the road area occupied by the abnormal event and the event processing time, and the severity is obtained by summing up based on the correspondence, severity = time required for the road management department to travel to the point where the abnormal event occurred + event processing time.

[0054] The affected vehicles are then determined based on the severity. Affected vehicles refer to vehicles that will pass through the section where the abnormal event is located before the abnormal event is completely handled. The supervision system can send a request message with the section where the abnormal event is located to the navigation platform, so that the navigation platform can determine all vehicles (hereinafter referred to as vehicles to be estimated) that include the section where the abnormal event is located in the navigation route and are about to pass through the section where the abnormal event is located, the vehicle locations, and the travel length of the aforementioned vehicles to be estimated from the section where the abnormal event is located.

[0055] The supervision system is used to receive the vehicles to be estimated and the travel lengths obtained by querying the navigation platform, and based on the current driving speed of the vehicles to be estimated, screen out the affected vehicles from the vehicles to be estimated. The affected vehicles meet the following conditions: the travel length between the affected vehicle and the road section described in the abnormal event / the current driving speed of the vehicle to be estimated ≤ the duration corresponding to the severity of the abnormal event.

[0056] In addition, the affected vehicles can be further divided into directly affected vehicles and indirectly affected vehicles according to the lane in which the abnormal event is located. Directly affected vehicles refer to affected vehicles whose current lane is consistent with the lane in which the abnormal event is located, and indirectly affected vehicles refer to affected vehicles whose current lane is different from the lane in which the abnormal event is located.

[0057] The supervision system will analyze the degree of impact of directly affected vehicles and indirectly affected vehicles respectively. For directly affected vehicles, the factors affecting their impact degree include at least the feasible journey length between the directly affected vehicles and the road section where the abnormal event is located. The feasible journey length refers to the journey length that the directly affected vehicles travel to the road section where the abnormal event is located when the vehicle speed is greater than 0; the shorter the feasible journey length, the greater the degree of impact.

[0058] For indirectly affected vehicles, the factors affecting their degree of impact include at least the vehicle density on the road section between the current position of the indirectly affected vehicle and the position of the abnormal event (hereinafter referred to as the evaluation section); the greater the vehicle density, the greater the degree of impact.

[0059] The monitoring system is used to determine whether the directly affected vehicle meets the avoidance conditions. The more directly affected the vehicle is, the higher the priority of the determination is, and the higher the corresponding determination frequency is. Exemplarily, the corresponding avoidance conditions are: the number of vehicles on the evaluation section between the location of the target directly affected vehicle and the location of the abnormal event, and in all lanes other than the affected lane where the target directly affected vehicle is located (hereinafter referred to as the evaluation lane), and the distance between vehicles on each evaluation lane (hereinafter referred to as the actual distance).

[0060] Based on the lane length occupied by the target affected vehicle when changing lanes in the historical period, determine whether there is an actual spacing greater than the lane length (hereinafter referred to as the selected vehicle spacing) on ​​the evaluation lane currently parallel to the affected lane where the target affected vehicle is located. If so, it is considered that the target affected vehicle meets the avoidance condition, and the rear vehicle of the two vehicles forming the aforementioned selected vehicle spacing is used as a reminder vehicle. Based on the current driving speed of the reminder vehicle, the avoidance period of the target affected vehicle is determined. The avoidance period is [current time, latest time], and the latest time = the time taken for the reminder vehicle to move to the specified distance behind the target affected vehicle. Then the monitoring system sends a reminder message with the avoidance period and avoidance plan to the target affected vehicle. The avoidance plan is specifically the evaluation lane where the reminder vehicle is located, so as to inform the target affected vehicle to change lanes to the corresponding evaluation period within the avoidance period. The monitoring system is also used to send a reminder message to the reminder vehicle to suggest that the reminder vehicle drive at the current speed to help the target affected vehicle avoid. Among them, the target affected vehicle refers to any directly affected vehicle.

[0061] Optionally, each of the preset road sections is pre-divided into a number of unit road sections; Regulatory approaches also include: At every designated period, determining a vehicle travel path of vehicles passing through each preset road section within the designated period; For each preset road section, determining the unit road sections in each preset road section that overlap with the vehicle driving path and the corresponding number of overlaps, determining the vehicle type corresponding to each vehicle driving path, and determining the benchmark score of each vehicle driving path according to the vehicle type; Calculate the maintenance score of each unit road section, and add all unit road sections with maintenance scores higher than the preset score to the preset maintenance list of the preset road section to which they belong; wherein the maintenance score is obtained by summing the benchmark scores of the formal paths overlapping with the corresponding unit road section.

[0062] Generate a road maintenance plan with a corresponding maintenance list for each preset road section.

[0063] In implementation, the supervision system determines the location information of all vehicles passing through each preset road section within the specified period at every specified period, and determines the vehicle driving path of each passing vehicle within the corresponding preset road section based on the location information. Determine the number of times each unit road section contained in each preset road section is run over by the passing vehicle within the specified period, that is, the number of times the unit road section and the vehicle driving path of the passing vehicle overlap, and perform weighted summation on the aforementioned overlap times to obtain the total number (i.e., the benchmark score), and the weight of the weighted summation is the benchmark score; specifically, for example, if a unit road section is run over by a vehicle 5 times, the vehicle type of each passing vehicle that is run over is determined separately, and the benchmark score for each run is determined based on the benchmark scores corresponding to different vehicle types, and the maintenance score can be obtained by summing up all the benchmark scores. Among them, the supervision system pre-stores the benchmark scores of different vehicle types, and the vehicle type is specifically a classification of vehicles based on vehicle volume.

[0064] Finally, the unit sections with maintenance scores higher than the preset scores (i.e., the unit sections that need maintenance) are added to the preset maintenance list of the preset sections to which they belong, and a section maintenance plan with a corresponding maintenance list is generated. Finally, the section maintenance plan for each preset section is displayed.

[0065] The present application also discloses a highway traffic incident monitoring system. Figure 3 ,include: Traffic data monitoring module 1, used for real-time monitoring and acquisition of highway traffic data based on preset radar; Abnormal event analysis module 2, used to analyze traffic data and determine whether an abnormal event has occurred; wherein the abnormal event at least includes traffic accidents and traffic jams; The abnormal event alarm module 3 is used to retrieve the monitoring video data of the highway section where the abnormal event occurs, generate and output alarm information with the monitoring video data and the traffic data corresponding to the abnormal event, so that the road management personnel can be informed of the alarm information; The abnormal event warning module 4 is used to determine whether there is a dangerous vehicle based on the traffic data obtained in real time; if there is a dangerous vehicle, the associated vehicle associated with the dangerous vehicle is determined in real time, and a warning message is sent to the navigation platform that is pre-communication-connected, so that the navigation platform displays the warning message in real time during the navigation process of the associated vehicle; wherein the warning message at least includes the azimuth relationship and vehicle distance information between the associated vehicle and the dangerous vehicle.

[0066] Optionally, the abnormal event warning module 4 is also used to retrieve, from a preset navigation platform, pre-screened vehicles whose navigation routes overlap with the navigation route of the dangerous vehicle based on the location of the dangerous vehicle; and is also used to screen out associated vehicles from the pre-screened vehicles based on the current vehicle speed of each pre-screened vehicle, the current vehicle speed of the dangerous vehicle, and the travel distance between the pre-screened vehicle and the dangerous vehicle; wherein the associated vehicles satisfy: the associated vehicles can travel on the corresponding section of the road where the route overlaps with the dangerous vehicle to within a specified range around the dangerous vehicle.

[0067] Optionally, it also includes an affected vehicle avoidance module, which is used to evaluate the severity of the abnormal event whenever it occurs, and determine the affected range of the abnormal event based on the severity, wherein the affected range at least includes affected lanes and affected vehicles; determine the degree of impact of each affected vehicle in real time, and based on the degree of impact, screen out avoiding vehicles that meet the avoidance conditions from the affected vehicles, as well as the avoidance time period in which each avoiding vehicle meets the avoidance conditions; send a reminder message with the avoidance time period and avoidance plan to the avoiding vehicle, so as to remind the avoiding vehicle to avoid the affected lanes within the avoidance time period.

[0068] Optionally, it also includes an abnormal event warning module, which is used to determine the risk factor of vehicles in each preset road section based on the traffic data of each preset road section obtained in real time, obtain the current environmental data of each preset road section, and the abnormal event history record of each preset road section, and use a pre-built prediction model to predict the probability of abnormal events in each preset road section in real time; it is also used to generate and output warning information when the probability of abnormal events corresponding to the first preset road section is higher than the preset probability, so that the drivers and passengers corresponding to the vehicles in the first preset road section can be informed of the warning information.

[0069] Optionally, an abnormal event animation simulation module is used to obtain vehicle driving data of vehicles involved in the abnormal event within a specified time period before and at the time of the abnormal event from real-time traffic data when an abnormal event occurs; it is also used to generate and output a simulation animation based on the vehicle driving data and the monitoring video data corresponding to the abnormal event, and the simulation animation is used to display the vehicle status of the vehicle involved before and after the abnormal event in the form of animation, and the vehicle status includes at least the vehicle position.

[0070] Optionally, the abnormal event animation simulation module is also used to determine the vehicle position information of the vehicle involved at each moment within a specified time period before the abnormal event occurs based on the vehicle driving data and the monitoring video data corresponding to the abnormal time, and generate a simulation animation for displaying the vehicle driving process; it is also used to determine the deformation of the impact position of the vehicle involved through a preset simulation model based on the vehicle speed of the vehicle involved at the time of the abnormal event and the impact position of the vehicle involved if the abnormal event is a traffic accident, and display the deformation of the impact position in the simulation animation.

[0071] Optionally, a road maintenance plan determination module is used to determine the vehicle travel path of vehicles passing through each preset road section within a specified period at every specified period; for each preset road section, determine the unit sections in each preset road section that overlap with the vehicle travel path, and the corresponding number of overlaps, and determine the road section maintenance plan for each preset road section based on the number of overlaps.

[0072] The embodiment of the present application also discloses a highway traffic incident monitoring device, which includes a memory and a processor. The memory stores a computer program that can be loaded by the processor and executes the above-mentioned highway traffic incident monitoring method.

[0073] The embodiment of the present application also discloses a computer-readable storage medium, which stores a computer program that can be loaded by a processor and execute the above-mentioned highway traffic incident supervision method. The computer-readable storage medium includes, for example: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0074] It should be noted that, in this document, relational terms such as first and second, etc. are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0075] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit the protection scope of the application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on these embodiments, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

Claims

1. A method for supervising highway traffic incidents, characterized in that: include: Based on the preset radar, real-time monitoring and acquisition of highway traffic data; Analyze the traffic data and determine whether an abnormal event occurs; wherein the abnormal event at least includes a traffic accident and a traffic jam; If an abnormal event occurs, the monitoring video data of the highway section where the abnormal event occurs is retrieved, and an alarm message containing the monitoring video data and the traffic data corresponding to the abnormal event is generated and output, so that the road management personnel are informed of the alarm message; Based on the traffic data acquired in real time, determining whether there is a dangerous vehicle; wherein the dangerous behavior of the dangerous vehicle includes pre-dangerous behavior and / or post-interference behavior; Predicting the driving trend and estimated driving behavior of each vehicle based on the current driving behavior of the vehicle, determining the feasibility of the estimated driving behavior, and if not feasible, determining the vehicle as a dangerous vehicle; If there is a dangerous vehicle, determine the associated vehicles related to the dangerous vehicle in real time; analyze the dangerous behavior of the dangerous vehicle and the driving behavior of the corresponding target vehicle, and filter out the associated vehicles whose corresponding driving behavior does not conflict with the dangerous behavior of the dangerous vehicle from the target vehicles; If there is a vehicle with a directional driving habit among the dangerous vehicle and the corresponding associated vehicles, the corresponding directional driving area is determined, and disturbed vehicles that are easily disturbed by the directional driving habit are screened out, wherein the disturbed vehicles at least include vehicles whose current driving routes intersect with the directional driving area and vehicles that have driving blind spots due to the dangerous vehicle moving into the directional driving area; the disturbed vehicles and the associated vehicles are combined as the associated vehicles of the dangerous vehicle; Generate warning information with a danger zone for each associated vehicle, predict an adjustment behavior of the associated vehicle based on the danger zone of the associated vehicle, and generate a buffer zone based on the adjustment behavior if the adjustment behavior meets a preset adjustment condition; The dangerous area and the buffer area are merged to generate warning information, and the vehicle navigation of the vehicle is controlled to display the corresponding warning information; if there are multiple overlapping dangerous areas and they belong to the same associated vehicle, the associated vehicle is determined as a dangerous vehicle; Whenever an abnormal event occurs, the severity of the abnormal event is evaluated, and the scope of the abnormal event is determined based on the severity, wherein the scope of the abnormal event at least includes the affected lanes and the affected vehicles; Determine the degree of impact of each affected vehicle in real time, and based on the degree of impact, select the evading vehicles that meet the avoidance conditions from the affected vehicles, and the avoidance period during which each of the evading vehicles meets the avoidance conditions; wherein the avoidance conditions are: based on the lane length occupied by the target affected vehicle when changing lanes in the historical period, determine whether there is an actual spacing greater than the lane length on the evaluation lane currently parallel to the affected lane where the target affected vehicle is located, if so, it is considered that the target affected vehicle meets the avoidance conditions; A reminder message with an avoidance period and an avoidance plan is sent to the avoidance vehicle to remind the avoidance vehicle to avoid the affected lane within the avoidance period.

2. The method for supervising highway traffic incidents according to claim 1, characterized in that: The traffic data at least includes vehicle driving data, and the real-time determination of the associated vehicle associated with the dangerous vehicle includes: Based on the location of the dangerous vehicle, retrieve pre-screened vehicles whose navigation routes overlap with the navigation route of the dangerous vehicle from a preset navigation platform; Based on the current vehicle speed of each pre-screened vehicle, the current vehicle speed of the dangerous vehicle, and the travel distance between the pre-screened vehicle and the dangerous vehicle, associated vehicles are screened out from the pre-screened vehicles; wherein the associated vehicles satisfy: the associated vehicles can travel to a specified range around the dangerous vehicle on a corresponding road section where there is an overlapping route with the dangerous vehicle.

3. The method for supervising highway traffic incidents according to claim 1, characterized in that: The traffic data at least includes vehicle driving data. The method further comprises: Based on the traffic data of each preset road section obtained in real time, determine the risk factor of vehicles in each preset road section, obtain the current environmental data of each preset road section, and the abnormal event history record of each preset road section, and use the pre-built prediction model to predict the probability of abnormal events in each preset road section in real time; When the probability of occurrence of an abnormal event corresponding to a first preset road section is higher than a preset probability, a warning message is generated and outputted so that the driver and passengers corresponding to the vehicle on the first preset road section can be informed of the warning message.

4. The method for supervising highway traffic incidents according to claim 1, characterized in that: The method further comprises: When an abnormal event occurs, obtaining vehicle travel data of vehicles involved in the abnormal event during a specified period before and when the abnormal event occurs from traffic data obtained in real time; Based on the vehicle driving data and the monitoring video data corresponding to the abnormal event, a simulation animation is generated and output, wherein the simulation animation is used to display the vehicle status of the vehicle involved before and after the abnormal event in an animated form, and the vehicle status includes at least the vehicle position.

5. The method for supervising highway traffic incidents according to claim 4, characterized in that: If the abnormal event is a traffic accident, the vehicle state also includes vehicle deformation; The generating and outputting a simulation animation based on the vehicle driving data and the monitoring video data corresponding to the abnormal event includes: Based on the vehicle driving data and the surveillance video data corresponding to the abnormal event, determine the vehicle position information of the vehicle involved at each moment in a specified time period before the abnormal event occurs, and generate a simulation animation for displaying the vehicle driving process; If the abnormal event is a traffic accident, the deformation of the impacted position of the vehicle involved is determined by a preset simulation model based on the vehicle speed of the vehicle involved when the abnormal event occurs and the impacted position of the vehicle involved, and the deformation of the impacted position is displayed in the simulation animation.

6. The method for supervising highway traffic incidents according to claim 3, characterized in that: Each of the preset road sections is pre-divided into a number of unit road sections; The method further comprises: At every designated period, determining a vehicle travel path of vehicles passing through each preset road section within the designated period; For each preset road section, the unit road sections in each preset road section that overlap with the vehicle driving path and the corresponding number of overlaps are determined, and based on the number of overlaps, the road section maintenance plan for each preset road section is determined.

7. A highway traffic incident supervision system, characterized in that: include, A traffic data monitoring module (1) is used to monitor and obtain the traffic data of the expressway in real time based on a preset radar; An abnormal event analysis module (2) is used to analyze the traffic data and determine whether an abnormal event has occurred; wherein the abnormal event at least includes a traffic accident and a traffic jam; An abnormal event alarm module (3) is used for, if an abnormal event occurs, retrieving monitoring video data of the expressway section where the abnormal event occurs, generating and outputting alarm information containing the monitoring video data and traffic data corresponding to the abnormal event, so that road management personnel are informed of the alarm information; The abnormal event warning module (4) is used to determine whether there is a dangerous vehicle based on traffic data acquired in real time; wherein the dangerous behavior of the dangerous vehicle includes pre-dangerous behavior and / or post-interference behavior; and is also used to predict the driving trend and estimated driving behavior of the vehicle based on the current driving behavior of each vehicle, determine the feasibility of the estimated driving behavior, and if it is not feasible, determine the vehicle as a dangerous vehicle; if there is a dangerous vehicle, determine in real time the associated vehicles related to the dangerous vehicle; analyze the dangerous behavior of the dangerous vehicle and the driving behavior of the corresponding target vehicle, and screen out the associated vehicles whose corresponding driving behavior does not conflict with the dangerous behavior of the dangerous vehicle from the target vehicles; if there is a vehicle with a biased driving habit among the dangerous vehicle and the corresponding associated vehicles, determine the corresponding biased driving area, and screen The disturbed vehicles that are susceptible to the deviated driving habit are identified, wherein the disturbed vehicles at least include vehicles whose current driving routes intersect with the deviated driving area and vehicles with driving blind spots caused by dangerous vehicles moving into the deviated driving area; the disturbed vehicles and associated vehicles are merged as associated vehicles of the dangerous vehicle; warning information with a dangerous area is generated for each associated vehicle, and based on the dangerous area of ​​the associated vehicle, the adjustment behavior of the associated vehicle is predicted, and if the adjustment behavior meets the preset adjustment conditions, a buffer area is generated based on the adjustment behavior; the dangerous area and the buffer area are merged to generate warning information, and the vehicle-mounted navigation of the vehicle is controlled to display the corresponding warning information; if there are multiple overlapping dangerous areas and they belong to the same associated vehicle, the associated vehicle is determined as a dangerous vehicle; The affected vehicle avoidance module is used to evaluate the severity of the abnormal event whenever it occurs, and determine the affected range of the abnormal event based on the severity, wherein the affected range at least includes the affected lanes and the affected vehicles; determine the affected degree of each affected vehicle in real time, and based on the affected degree, screen out the avoiding vehicles that meet the avoidance conditions from the affected vehicles, as well as the avoidance time period during which each avoiding vehicle meets the avoidance conditions; send a reminder message with the avoidance time period and the avoidance plan to the avoiding vehicle, so as to remind the avoiding vehicle to avoid the affected lane within the avoidance time period.

8. A monitoring device for highway traffic incidents, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute any one of the methods according to claims 1 to 6.

9. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute any one of the methods as claimed in claims 1 to 6.

Images