Intelligent monitoring method and system based on expressway entrance

Abstract

The invention relates to the technical field of traffic monitoring, and particularly discloses an intelligent monitoring method and system based on a highway entrance, and the method comprises the steps: obtaining a vehicle driving stable value based on a vehicle confluence abnormal signal, comparing the vehicle driving stable value with a threshold value, generating a signal whether vehicle driving is stable or not, obtaining a confluence region accident occurrence probability value based on a vehicle driving unstable signal, and obtaining a vehicle confluence region accident occurrence probability value; the method comprises the following steps: monitoring vehicle running stability, comparing the vehicle running stability with a threshold value, generating an accident occurrence probability signal, adjusting the vehicle confluence running speed based on the accident occurrence probability signal, obtaining a confluence running speed adjustment value, and completing optimization and adjustment of vehicle confluence running, the vehicle running stability is monitored, and the confluence running speed is adjusted when the vehicle running stability is detected to be unstable. Therefore, the accident risk in the confluence area caused by out-of-control or improper operation of the vehicle can be effectively reduced, and the traffic jam caused by the accident is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic monitoring, and in particular to an intelligent monitoring method and system based on a highway entrance. Background Art

[0002] With the continuous growth of traffic flow and the improvement of highway networks, real-time monitoring and management of highway entrances and exits have become particularly important. Intelligent monitoring methods and systems based on highway entrances have emerged. By integrating advanced sensor technology, data processing technology and communication technology, it can realize real-time monitoring and analysis of vehicle flow, speed, driving trajectory and other information at highway entrances, provide effective decision-making support for traffic management departments, and improve the traffic efficiency and safety of highways.

[0003] The Chinese invention patent with publication number CN110503826B discloses an intelligent induction method based on high-speed flow monitoring and prediction. It uses a new model algorithm to predict traffic flow based on real-time monitoring of traffic status. Then, based on the prediction results and combined with relevant highway design and management plans, it is released in accordance with the high-speed induction information release process. At the same time, the traffic flow status is monitored in real time, the induction results are evaluated, and finally the results are fed back to update the induction knowledge base.

[0004] However, there is no monitoring equipment to collect real-time traffic data in the merging area to reflect the actual traffic conditions in the area and avoid traffic accidents in the future. There is no monitoring of vehicle driving stability and adjustment of merging speed when instability is detected, which can effectively reduce the risk of accidents in the merging area due to vehicle loss of control or improper operation, and reduce traffic congestion caused by accidents. Summary of the invention

[0005] The object of the present invention is to provide an intelligent monitoring method and system based on a high-speed entrance to solve the technical problems in the above background.

[0006] The purpose of the present invention can be achieved by the following technical solutions: In a first aspect, the present invention provides an intelligent monitoring method based on a high-speed entrance, comprising the following steps: Step 1: Use monitoring equipment to monitor the merging area before the highway entrance, obtain the regional congestion value, compare it with the threshold, and generate a signal to determine whether the area is congested; If the regional congestion value is greater than or equal to the regional congestion threshold, a regional congestion signal is generated; Step 2: Based on the regional congestion signal, obtain the vehicle merging value, compare it with the threshold, and generate a signal whether the vehicle merging is abnormal; If the vehicle merging value is greater than or equal to the vehicle merging threshold, a vehicle merging abnormality signal is generated, and the vehicle generating the vehicle merging abnormality signal is marked as a merging abnormality vehicle; Step 3: Based on the abnormal vehicle merging signal, obtain the vehicle driving stability value, compare it with the threshold, and generate a vehicle driving stability signal; If the vehicle driving stability value is greater than or equal to the vehicle driving stability threshold, a vehicle driving instability signal is generated; Step 4: Based on the unstable vehicle driving signal, obtain the probability value of the accident in the merging area, compare it with the threshold, and generate an accident probability signal; If the probability value of an accident occurring in the merging area is greater than or equal to the threshold value of the probability value of an accident occurring in the merging area, a large signal of the probability of an accident occurring is generated; Step 5: Based on the large signal of the accident probability, the merging speed of the vehicle is adjusted to obtain the merging speed adjustment value, thereby completing the optimization adjustment of the merging speed of the vehicle; In step 5, when a high accident probability signal is generated, the merging driving of the vehicles is adjusted, and the driving speed of the vehicles in the merging area is multiplied by the adjustment coefficient to obtain the merging driving speed adjustment value; The adjustment coefficient is obtained as follows: The vehicle driving stability deviation coefficient and the merging area accident occurrence deviation coefficient are obtained, and the vehicle driving stability deviation coefficient and the merging area accident occurrence deviation coefficient are added together to obtain an adjustment coefficient.

[0007] As a further solution of the present invention: in step 1, the regional congestion value is obtained in the following manner: During the monitoring period, the area occupied by each vehicle in the merging area is obtained, and the areas occupied by all vehicles in the merging area are added together to obtain the total area occupied by vehicles in the merging area; The area of ​​the merging area is obtained, and the ratio of the total area occupied by vehicles in the merging area to the area of ​​the merging area is calculated to obtain the regional congestion value.

[0008] As a further solution of the present invention: in step 2, the vehicle merging value is obtained in the following manner: During the monitoring period, the vehicle area driving speed and the vehicle path deviation value are obtained, and the vehicle area driving speed and the vehicle path deviation value are added and summed to obtain the vehicle merging value; The vehicle regional driving speed is obtained as follows: In the merging area, the vehicle speed is monitored in real time, and the vehicle speeds are added and averaged to obtain the vehicle area speed.

[0009] As a further solution of the present invention: in step 2, the vehicle path deviation value is obtained in the following manner: In the merging area, the merging area is divided into grids, and the actual position coordinates of the vehicles in the merging area are marked as ( ), mark the vehicle preset position coordinates as ( ), obtain the initial position of the vehicle in the merging area, and mark the coordinates of the initial position of the vehicle as ( ); During the monitoring period, the actual position coordinates of the vehicles in the merging area are monitored in real time ( ), divide the monitoring period into several time nodes, and obtain the actual position coordinates of the vehicle corresponding to each time node ( ), connect the actual position coordinates of the vehicle corresponding to each time node to obtain the actual driving path of the vehicle; Based on the actual driving path of the vehicle, the actual driving path of the vehicle is compared with the preset driving path of the vehicle. The comparison process is as follows: The actual position coordinates of the vehicle corresponding to each time node are subtracted from the preset position coordinates of the vehicle to obtain the vehicle position deviation value; The vehicle position deviation values ​​are added and averaged to obtain the vehicle path deviation value.

[0010] As a further solution of the present invention: in step 3, the vehicle driving stability value is obtained in the following manner: During the monitoring period, the number of hasty vehicle driving and the number of vehicle derailment in the merging area are obtained, and the number of hasty vehicle driving and the number of vehicle derailment are added together to obtain the vehicle driving stability value.

[0011] As a further solution of the present invention: in step 3, the process of obtaining the number of hasty vehicle driving times is as follows: During the monitoring period, the real-time speed of the abnormal merging vehicle is obtained, and an XY axis coordinate system is established. The X axis represents the monitoring time point, and the Y axis represents the speed of the abnormal merging vehicle corresponding to each monitoring time point during the monitoring period. The real-time speed of the abnormal merging vehicle is substituted into the XY axis coordinate system to obtain the real-time speed change curve of the abnormal merging vehicle; Based on the real-time speed change curve of the abnormal merging vehicle, the peak coordinate value in the real-time speed change curve of the abnormal merging vehicle is extracted and marked as ( , ), the trough coordinate value, marked as ( , ); Calculate the distance between the coordinate values ​​of two adjacent wave crests and the coordinate values ​​of wave troughs to obtain the speed change value; The speed change value is compared with the speed change threshold. The comparison process is as follows: If the speed change value is greater than or equal to the speed change threshold, the probability of rush is high, and the time period is marked as a rush time period; The number of times the hasty vehicle time period appears in the real-time speed change curve of the abnormal merging vehicles is obtained, and the number of hasty vehicle driving times is obtained.

[0012] As a further solution of the present invention: in step 3, the number of times the vehicle deviates from the track is obtained as follows: Based on the vehicle position deviation value in the above step 2, the vehicle position deviation values ​​in the monitoring period are added and averaged to obtain the vehicle position deviation threshold; The vehicle position deviation value is compared with the vehicle position deviation threshold. The comparison process is as follows: If the vehicle position deviation value is greater than or equal to the vehicle position deviation threshold, the time point at which the position deviation large signal is generated is marked as the position deviation time point; If the vehicle position deviation value is less than the vehicle position deviation threshold, the time period in which the position deviation small signal is generated is marked as a non-position deviation time point; The number of position deviation time points within the monitoring period is obtained to obtain the number of times the vehicle deviates from the track.

[0013] As a further solution of the present invention: in step 4, the method of obtaining the probability value of the accident occurrence in the merging area is: Obtaining the impact value of the number of abnormal merging vehicles and the impact value of the time of abnormal merging vehicles, adding the impact value of the number of abnormal merging vehicles and the impact value of the time of abnormal merging vehicles to obtain the probability value of an accident occurring in the merging area; The process of obtaining the impact value of the number of abnormal merging vehicles is as follows: During the monitoring period, the vehicle area ratio affected by the abnormal merging vehicle and the area ratio of the abnormal merging vehicle are obtained, and the vehicle area ratio affected by the abnormal merging vehicle and the area ratio of the abnormal merging vehicle are added together to obtain the impact value of the number of abnormal merging vehicles; The process of obtaining the area ratio of abnormal merging vehicles is as follows: During the monitoring period, the area occupied by the abnormal merging vehicle is obtained, and the area occupied by the abnormal merging vehicle is calculated to be a ratio of the area occupied by the abnormal merging vehicle to the area occupied by the vehicle, so as to obtain the abnormal merging vehicle area ratio; The process of obtaining the area ratio of vehicles affected by abnormal merging vehicles is as follows: During the monitoring period, the vehicle area affected by the abnormal merging vehicle is obtained, and the ratio of the vehicle area affected by the abnormal merging vehicle to the area occupied by the vehicle is calculated to obtain the vehicle area ratio affected by the abnormal merging vehicle.

[0014] As a further explanation of the present invention: in step 4, the acquisition method of the time impact value of the abnormal merging vehicle is as follows: During the monitoring period, the length of time for the abnormal merging vehicle to pass and the length of time for the abnormal merging vehicle to affect the vehicle to pass are obtained, and the length of time for the abnormal merging vehicle to pass and the length of time for the abnormal merging vehicle to affect the vehicle to pass are added together to obtain the time impact value of the abnormal merging vehicle; The process of obtaining the length of time for abnormal merging vehicles is as follows: During the monitoring period, the travel time of abnormal merging vehicles in the merging area is obtained, and the travel time of abnormal merging vehicles is added up to obtain the total travel time of abnormal merging vehicles; The total time of abnormal merging vehicles passing is calculated by ratio with the monitoring cycle time to obtain the length of the abnormal merging vehicle passing time; The process of obtaining the length of time that abnormal merging vehicles affect the passage of vehicles is as follows: During the monitoring period, the time that the abnormal merging vehicles affect the passage of vehicles is obtained, and the time that the abnormal merging vehicles affect the passage of vehicles is added up to obtain the total time that the abnormal merging vehicles affect the passage of vehicles; The total time that the abnormal merging vehicle affects the passage of vehicles is calculated by ratio with the monitoring cycle time, so as to obtain the length of time that the abnormal merging vehicle affects the passage of vehicles; The process of determining the vehicles affected by the abnormal merging vehicle is as described above in the process of obtaining the area ratio of the vehicles affected by the abnormal merging vehicle.

[0015] In a second aspect, the present invention provides an intelligent monitoring system based on a high-speed entrance, the system comprising the following modules: Congestion monitoring module: monitors the merging area before the highway entrance through monitoring equipment, obtains the regional congestion value, compares it with the threshold, and generates a signal whether the area is congested; If the regional congestion value is greater than or equal to the regional congestion threshold, a regional congestion signal is generated; Merging analysis module: Based on the regional congestion signal, the vehicle merging value is obtained, compared with the threshold, and a signal is generated to determine whether the vehicle merging is abnormal; If the vehicle merging value is greater than or equal to the vehicle merging threshold, a vehicle merging abnormality signal is generated, and the vehicle generating the vehicle merging abnormality signal is marked as a merging abnormality vehicle; Stability assessment module: Based on the abnormal vehicle merging signal, obtain the vehicle driving stability value, compare it with the threshold, and generate a signal to determine whether the vehicle is stable; If the vehicle driving stability value is greater than or equal to the vehicle driving stability threshold, a vehicle driving instability signal is generated; Probability prediction module: Based on the unstable vehicle driving signal, the probability value of the accident in the merging area is obtained, compared with the threshold, and the probability signal of the accident is generated; If the probability value of an accident occurring in the merging area is greater than or equal to the threshold value of the probability value of an accident occurring in the merging area, a large signal of the probability of an accident occurring is generated; Optimization and adjustment module: Based on the large signal of accident probability, the merging speed of vehicles is adjusted to obtain the merging speed adjustment value, thus completing the optimization and adjustment of the merging speed of vehicles; In step 5, when a high accident probability signal is generated, the merging driving of the vehicles is adjusted, and the driving speed of the vehicles in the merging area is multiplied by the adjustment coefficient to obtain the merging driving speed adjustment value; The adjustment coefficient is obtained as follows: The vehicle driving stability deviation coefficient and the merging area accident occurrence deviation coefficient are obtained, and the vehicle driving stability deviation coefficient and the merging area accident occurrence deviation coefficient are added together to obtain an adjustment coefficient.

[0016] Beneficial effects of the present invention: (1) The present invention monitors the merging area before the highway entrance through a monitoring device, obtains the regional congestion value, compares it with the threshold, generates a signal whether the area is congested, and obtains the vehicle merging value based on the regional congestion signal, compares it with the threshold, and generates a signal whether the vehicle merging is abnormal. The monitoring device can collect traffic data of the merging area in real time, reflect the actual traffic conditions in the area, and avoid traffic accidents in the later stage; (2) The present invention obtains a vehicle driving stability value based on a vehicle merging abnormal signal, compares it with a threshold value, and generates a vehicle driving stability signal. Based on a vehicle driving instability signal, the present invention obtains a probability value of an accident occurring in the merging area, compares it with a threshold value, and generates an accident occurrence probability signal. Based on the large accident occurrence probability signal, the present invention adjusts the vehicle merging speed to obtain a merging speed adjustment value, thereby completing the optimization adjustment of the vehicle merging. By monitoring the vehicle driving stability and adjusting the merging speed when instability is detected, the risk of accidents in the merging area caused by vehicle loss of control or improper operation can be effectively reduced, thereby reducing traffic congestion caused by accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention will be further described below in conjunction with the accompanying drawings.

[0018] Figure 1 is a flow chart of Embodiment 1 of the present invention; Figure 2 is a flow chart of Embodiment 2 of the present invention; Figure 3 It is a schematic diagram of the system of the present invention. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] Embodiment 1: See also Figure 1 As shown, an intelligent monitoring method based on a high-speed entrance according to an embodiment of the present invention is specifically described as follows: Step 1: Use monitoring equipment to monitor the merging area before the highway entrance, obtain the regional congestion value, compare it with the threshold, and generate a signal to determine whether the area is congested; In some embodiments, the merging area before the highway entrance is detected by a monitoring device to obtain a regional congestion value, and the regional congestion value is compared with the regional congestion threshold. The comparison process is as follows: If the regional congestion value is greater than or equal to the regional congestion threshold, it means that there are a large number of vehicles in the merging area and the safe distance between vehicles is small, and a regional congestion signal is generated; If the regional congestion value is less than the regional congestion threshold, it means that the number of vehicles in the merging area is small and the safe distance between vehicles is large, and a regional non-congestion signal is generated; The regional congestion value is obtained as follows: During the monitoring period, the area occupied by each vehicle in the merging area is obtained, and the areas occupied by all vehicles in the merging area are added together to obtain the total area occupied by vehicles in the merging area; The area of ​​the merging area is obtained, and the ratio of the total area occupied by vehicles in the merging area to the area of ​​the merging area is calculated to obtain the regional congestion value; Step 2: Based on the regional congestion signal, obtain the vehicle merging value, compare it with the threshold, and generate a signal whether the vehicle merging is abnormal; Wherein, whether the vehicle merging is abnormal signal includes a vehicle merging abnormal signal and a vehicle merging normal signal; In some embodiments, when a regional congestion signal is generated, a vehicle merging value is obtained, and the vehicle merging value is compared with a vehicle merging threshold. The comparison process is as follows: If the vehicle merging value is greater than or equal to the vehicle merging threshold, it means that the vehicle speed is fast and the vehicle path deviation is large, and a vehicle merging abnormality signal is generated, and the vehicle generating the vehicle merging abnormality signal is marked as a merging abnormality vehicle; If the vehicle merging value is less than the vehicle merging threshold, it means that the vehicle speed is slow and the vehicle path deviation is small, and a vehicle merging normal signal is generated, and the vehicle generating the vehicle merging normal signal is marked as a merging normal vehicle; The vehicle merging value is obtained as follows: During the monitoring period, the vehicle area driving speed and the vehicle path deviation value are obtained, and the vehicle area driving speed and the vehicle path deviation value are added and summed to obtain the vehicle merging value; Exemplarily, the vehicle regional travel speed is obtained in the following manner: In the merging area, the vehicle speed is monitored in real time, and the vehicle speeds are added and averaged to obtain the vehicle area speed; The vehicle path deviation value is obtained as follows: In the merging area, the merging area is divided into grids, and the actual position coordinates of the vehicles in the merging area are marked as ( ), mark the vehicle preset position coordinates as ( ), obtain the initial position of the vehicle in the merging area, and mark the coordinates of the initial position of the vehicle as ( ); Among them, it is necessary to explain: ) is marked as the position reached by the vehicle in the merging area at each time point during the monitoring period, and n can be 1, 2, 3, ...; During the monitoring period, the actual position coordinates of the vehicles in the merging area are monitored in real time ( ), divide the monitoring period into several time nodes, and obtain the actual position coordinates of the vehicle corresponding to each time node ( ), connect the actual position coordinates of the vehicle corresponding to each time node to obtain the actual driving path of the vehicle; Based on the actual driving path of the vehicle, the actual driving path of the vehicle is compared with the preset driving path of the vehicle. The comparison process is as follows: The actual position coordinates of the vehicle corresponding to each time node are subtracted from the preset position coordinates of the vehicle to obtain the vehicle position deviation value; The vehicle position deviation values ​​are added and averaged to obtain the vehicle path deviation value; Specific implementation plan of the embodiment of the present invention: monitor the merging area before the highway entrance through a monitoring device, obtain the regional congestion value, compare it with the threshold, generate a signal whether the area is congested, and based on the regional congestion signal, obtain the vehicle merging value, compare it with the threshold, and generate a signal whether the vehicle merging is abnormal. The monitoring device can collect traffic data of the merging area in real time, reflect the actual traffic conditions in the area, and avoid traffic accidents in the future.

[0021] Embodiment 2: Based on Example 1, please refer to Figure 2As shown, the intelligent monitoring method based on the high-speed entrance described in the embodiment of the present invention also includes the following steps: Step 3: Based on the abnormal vehicle merging signal, obtain the vehicle driving stability value, compare it with the threshold, and generate a vehicle driving stability signal; In some embodiments, when a vehicle merging abnormality signal is generated, a vehicle driving stability value is obtained, and the vehicle driving stability value is compared with a vehicle driving stability threshold. The comparison process is as follows: If the vehicle driving stability value is greater than or equal to the vehicle driving stability threshold, it means that the vehicle has been in a hurry many times and has deviated from the track many times during driving, and a vehicle driving instability signal is generated; If the vehicle driving stability value is less than the vehicle driving stability threshold, it means that the vehicle has fewer hasty times and fewer derailment times during driving, and a vehicle driving stability signal is generated; Among them, the vehicle driving stability value is obtained as follows: During the monitoring period, the number of hasty vehicle driving and the number of vehicle derailment in the merging area are obtained, and the number of hasty vehicle driving and the number of vehicle derailment are added together to obtain the vehicle driving stability value; Exemplarily, the process of obtaining the number of times a vehicle travels in a hurry is as follows: During the monitoring period, the real-time speed of the abnormal merging vehicle is obtained, and an XY axis coordinate system is established. The X axis represents the monitoring time point, and the Y axis represents the speed of the abnormal merging vehicle corresponding to each monitoring time point during the monitoring period. The real-time speed of the abnormal merging vehicle is substituted into the XY axis coordinate system to obtain the real-time speed change curve of the abnormal merging vehicle; Based on the real-time speed change curve of the abnormal merging vehicle, the peak coordinate value in the real-time speed change curve of the abnormal merging vehicle is extracted and marked as ( , ), the trough coordinate value, marked as ( , ); Calculate the distance between the coordinate values ​​of two adjacent wave crests and the coordinate values ​​of wave troughs to obtain the speed change value; The speed change value is compared with the speed change threshold. The comparison process is as follows: If the speed change value is greater than or equal to the speed change threshold, it means that the speed change of the abnormal merging vehicle is large and the probability of haste is high, and the time period is marked as hasty vehicle time period; If the speed change value is less than the speed change threshold, it means that the speed change of the abnormal merging vehicle is small and the probability of rushing is small, so the time period is marked as the non-rushing vehicle time period; Obtain the number of times the hasty vehicle time period appears in the real-time speed change curve of the abnormal merging vehicles, and obtain the number of hasty vehicle driving times; The method for obtaining the number of vehicle derailment times is as follows: Based on the vehicle position deviation value in the above step 2, the vehicle position deviation values ​​in the monitoring period are added and averaged to obtain the vehicle position deviation threshold; The vehicle position deviation value is compared with the vehicle position deviation threshold. The comparison process is as follows: If the vehicle position deviation value is greater than or equal to the vehicle position deviation threshold, it means that the actual driving path of the merging vehicle deviates greatly from the safe driving path, and a large position deviation signal is generated, and the time point when the large position deviation signal is generated is marked as the position deviation time point; If the vehicle position deviation value is less than the vehicle position deviation threshold, it means that the actual driving path of the merging vehicle deviates slightly from the safe driving path, and a small position deviation signal is generated. The time period when the small position deviation signal is generated is marked as a non-position deviation time point; Obtain the number of position deviation time points within the monitoring period and obtain the number of times the vehicle deviates from the track; Step 4: Based on the unstable vehicle driving signal, obtain the probability value of the accident in the merging area, compare it with the threshold, and generate an accident probability signal; Among them, the accident probability signal includes a large accident probability signal and a small accident probability signal; In some embodiments, when a vehicle driving instability signal is generated, a merging area accident probability value is obtained, and the merging area accident probability value is compared with a merging area accident probability threshold, and the comparison process is as follows: If the probability value of an accident in the merging area is greater than or equal to the threshold value of the probability value of an accident in the merging area, it means that the probability of an accident in the merging area caused by the abnormal merging vehicle is relatively high, and a high probability signal of an accident is generated; If the probability value of an accident in the merging area is less than the threshold value of the probability of an accident in the merging area, it means that the probability of an accident in the merging area caused by an abnormal merging vehicle is small, and a small signal of the probability of the accident mode is generated; The method for obtaining the probability value of an accident in the merging area is as follows: Obtain the impact value of the number of abnormal merging vehicles and the ratio of the travel time of abnormal merging vehicles, add the ratio of the number of abnormal merging vehicles and the ratio of the travel time of abnormal merging vehicles to obtain the probability value of the accident occurring in the merging area; The process of obtaining the impact value of the number of abnormal merging vehicles is as follows: During the monitoring period, the vehicle area ratio affected by the abnormal merging vehicle and the area ratio of the abnormal merging vehicle are obtained, and the vehicle area ratio affected by the abnormal merging vehicle and the area ratio of the abnormal merging vehicle are added together to obtain the impact value of the number of abnormal merging vehicles; Exemplarily, the process of obtaining the area ratio of the abnormal merging vehicle is as follows: During the monitoring period, the area occupied by the abnormal merging vehicle is obtained, and the area occupied by the abnormal merging vehicle is calculated to be a ratio of the area occupied by the abnormal merging vehicle to the area occupied by the vehicle, so as to obtain the abnormal merging vehicle area ratio; The process of obtaining the area ratio of vehicles affected by abnormal merging vehicles is as follows: During the monitoring period, the vehicle area affected by the abnormal merging vehicle is obtained, and the vehicle area affected by the abnormal merging vehicle is calculated to be a ratio of the vehicle area affected by the abnormal merging vehicle to the area occupied by the vehicle, so as to obtain the vehicle area ratio affected by the abnormal merging vehicle; Specifically, the process of determining whether an abnormal merging vehicle affects another vehicle is as follows: During the monitoring period, the driving stability values ​​of vehicles around the abnormal merging vehicle are obtained with the abnormal merging vehicle as the center, and marked as the vehicle abnormal value to be waited; The vehicle abnormal value is compared with the vehicle abnormal threshold. The comparison process is as follows: If the vehicle waiting abnormality value is greater than or equal to the vehicle waiting abnormality threshold, it means that the vehicles around the merging abnormal vehicle are driving unstably, and a waiting abnormality signal is generated, and the vehicle corresponding to the generated waiting abnormality signal is marked as a merging abnormal vehicle affecting the vehicle; If the vehicle waiting abnormality value is less than the vehicle waiting abnormality threshold, it means that the vehicles around the merging abnormal vehicle are running stably, and a non-waiting abnormality signal is generated, and the vehicle corresponding to the non-waiting abnormality signal is marked as a non-merging abnormal vehicle affecting the vehicle; The process of obtaining the time impact value of abnormal merging vehicles is as follows: During the monitoring period, the length of time for the abnormal merging vehicle to pass and the length of time for the abnormal merging vehicle to affect the vehicle to pass are obtained, and the length of time for the abnormal merging vehicle to pass and the length of time for the abnormal merging vehicle to affect the vehicle to pass are added together to obtain the time impact value of the abnormal merging vehicle; Exemplarily, the process of obtaining the length of time for merging abnormal vehicles is as follows: During the monitoring period, the travel time of abnormal merging vehicles in the merging area is obtained, and the travel time of abnormal merging vehicles is added up to obtain the total travel time of abnormal merging vehicles; The total time of abnormal merging vehicles passing is calculated by ratio with the monitoring cycle time to obtain the length of the abnormal merging vehicle passing time; The process of obtaining the length of time that abnormal merging vehicles affect the passage of vehicles is as follows: During the monitoring period, the time that the abnormal merging vehicles affect the passage of vehicles is obtained, and the time that the abnormal merging vehicles affect the passage of vehicles is added up to obtain the total time that the abnormal merging vehicles affect the passage of vehicles; The total time that the abnormal merging vehicle affects the passage of vehicles is calculated by ratio with the monitoring cycle time, so as to obtain the length of time that the abnormal merging vehicle affects the passage of vehicles; The process of determining the vehicles affected by the abnormal merging vehicle is as described above in the process of obtaining the area ratio of the vehicles affected by the abnormal merging vehicle; Step 5: Based on the large signal of the accident probability, the merging speed of the vehicle is adjusted to obtain the merging speed adjustment value, thereby completing the optimization adjustment of the merging speed of the vehicle; In some embodiments, when a high accident probability signal is generated, the merging driving of the vehicle is adjusted, and the driving speed of the vehicle in the merging area is multiplied by the adjustment coefficient to obtain the merging driving speed adjustment value; The adjustment coefficient is obtained as follows: Obtaining a vehicle driving stability deviation coefficient and a merging area accident occurrence deviation coefficient, adding the vehicle driving stability deviation coefficient and the merging area accident occurrence deviation coefficient to obtain an adjustment coefficient; Exemplarily, the process of obtaining the vehicle driving stability deviation coefficient is as follows: Obtaining a vehicle driving stability value, subtracting the vehicle driving stability value from a vehicle driving stability threshold value, and obtaining a vehicle driving stability deviation value; The vehicle driving stability deviation value is calculated by ratio with the vehicle driving stability threshold value to obtain the vehicle driving stability deviation coefficient; The process of obtaining the accident occurrence deviation coefficient in the merging area is as follows: Obtaining a probability value of an accident occurring in the merging area, subtracting the probability value of an accident occurring in the merging area from a threshold value of an accident occurring in the merging area, and obtaining a deviation value of the probability of an accident occurring in the merging area; The merging area accident occurrence probability deviation value is compared with the merging area accident occurrence probability threshold value to obtain the merging area accident occurrence deviation coefficient; Specific implementation scheme of the embodiment of the present invention: based on the vehicle merging abnormal signal, the vehicle driving stability value is obtained, compared with the threshold value, and a signal of whether the vehicle driving is stable is generated; based on the vehicle driving unstable signal, the probability value of an accident occurrence in the merging area is obtained, compared with the threshold value, and a signal of the size of the accident occurrence probability is generated; based on the large signal of the accident occurrence probability, the vehicle merging speed is adjusted to obtain the merging speed adjustment value, and the optimization adjustment of the vehicle merging driving is completed; by monitoring the vehicle driving stability and adjusting the merging speed when instability is detected, the risk of accidents in the merging area caused by vehicle loss of control or improper operation can be effectively reduced, and traffic congestion caused by accidents can be reduced.

[0022] Embodiment three: Based on the first and second embodiments, please refer to Figure 3 As shown, an intelligent monitoring system based on a highway entrance according to an embodiment of the present invention includes the following steps: Congestion monitoring module: monitors the merging area before the highway entrance through monitoring equipment, obtains the regional congestion value, compares it with the threshold, and generates a signal whether the area is congested; If the regional congestion value is greater than or equal to the regional congestion threshold, a regional congestion signal is generated; Merging analysis module: Based on the regional congestion signal, the vehicle merging value is obtained, compared with the threshold, and a signal is generated to determine whether the vehicle merging is abnormal; If the vehicle merging value is greater than or equal to the vehicle merging threshold, a vehicle merging abnormality signal is generated, and the vehicle generating the vehicle merging abnormality signal is marked as a merging abnormality vehicle; Stability assessment module: Based on the abnormal vehicle merging signal, obtain the vehicle driving stability value, compare it with the threshold, and generate a signal to determine whether the vehicle is stable; If the vehicle driving stability value is greater than or equal to the vehicle driving stability threshold, a vehicle driving instability signal is generated; Probability prediction module: Based on the unstable vehicle driving signal, the probability value of the accident in the merging area is obtained, compared with the threshold, and the probability signal of the accident is generated; If the probability value of an accident occurring in the merging area is greater than or equal to the threshold value of the probability value of an accident occurring in the merging area, a large signal of the probability of an accident occurring is generated; Optimization and adjustment module: Based on the large signal of accident probability, the merging speed of vehicles is adjusted to obtain the merging speed adjustment value, thus completing the optimization and adjustment of the merging speed of vehicles; In step 5, when a high accident probability signal is generated, the merging driving of the vehicles is adjusted, and the driving speed of the vehicles in the merging area is multiplied by the adjustment coefficient to obtain the merging driving speed adjustment value; The adjustment coefficient is obtained as follows: The vehicle driving stability deviation coefficient and the merging area accident occurrence deviation coefficient are obtained, and the vehicle driving stability deviation coefficient and the merging area accident occurrence deviation coefficient are added together to obtain an adjustment coefficient.

[0023] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. An intelligent monitoring method based on high-speed entrance, characterized in that: The following steps are involved: Step 1: Use monitoring equipment to monitor the merging area before the highway entrance, obtain the regional congestion value, compare it with the threshold, and generate a signal to determine whether the area is congested; If the regional congestion value is greater than or equal to the regional congestion threshold, a regional congestion signal is generated; Step 2: Based on the regional congestion signal, obtain the vehicle merging value, compare it with the threshold, and generate a signal whether the vehicle merging is abnormal; If the vehicle merging value is greater than or equal to the vehicle merging threshold, a vehicle merging abnormality signal is generated, and the vehicle generating the vehicle merging abnormality signal is marked as a merging abnormality vehicle; Step 3: Based on the abnormal vehicle merging signal, obtain the vehicle driving stability value, compare it with the threshold, and generate a vehicle driving stability signal; If the vehicle driving stability value is greater than or equal to the vehicle driving stability threshold, a vehicle driving instability signal is generated; Step 4: Based on the unstable vehicle driving signal, obtain the probability value of the accident in the merging area, compare it with the threshold, and generate an accident probability signal; If the probability value of an accident occurring in the merging area is greater than or equal to the threshold value of the probability value of an accident occurring in the merging area, a large signal of the probability of an accident occurring is generated; Step 5: Based on the large signal of the accident probability, the merging speed of the vehicle is adjusted to obtain the merging speed adjustment value, thereby completing the optimization adjustment of the merging speed of the vehicle; In step 5, when a high accident probability signal is generated, the merging driving of the vehicles is adjusted, and the driving speed of the vehicles in the merging area is multiplied by the adjustment coefficient to obtain the merging driving speed adjustment value; The adjustment coefficient is obtained as follows: The vehicle driving stability deviation coefficient and the merging area accident occurrence deviation coefficient are obtained, and the vehicle driving stability deviation coefficient and the merging area accident occurrence deviation coefficient are added together to obtain an adjustment coefficient.

2. The intelligent monitoring method based on high-speed entrance according to claim 1 is characterized in that: In step 1, the regional congestion value is obtained as follows: During the monitoring period, the area occupied by each vehicle in the merging area is obtained, and the areas occupied by all vehicles in the merging area are added together to obtain the total area occupied by vehicles in the merging area; The area of ​​the merging area is obtained, and the ratio of the total area occupied by vehicles in the merging area to the area of ​​the merging area is calculated to obtain the regional congestion value.

3. The intelligent monitoring method based on high-speed entrance according to claim 1 is characterized in that: In step 2, the vehicle merging value is obtained as follows: During the monitoring period, the vehicle area driving speed and the vehicle path deviation value are obtained, and the vehicle area driving speed and the vehicle path deviation value are added and summed to obtain the vehicle merging value; The vehicle regional driving speed is obtained as follows: In the merging area, the vehicle speed is monitored in real time, and the vehicle speeds are added and averaged to obtain the vehicle area speed.

4. The intelligent monitoring method based on high-speed entrance according to claim 3 is characterized in that: In step 2, the vehicle path deviation value is obtained as follows: In the merging area, the merging area is divided into grids, and the actual position coordinates of the vehicles in the merging area are marked as ( ), mark the vehicle preset position coordinates as ( ), obtain the initial position of the vehicle in the merging area, and mark the coordinates of the initial position of the vehicle as ( ); During the monitoring period, the actual position coordinates of the vehicles in the merging area are monitored in real time ( ), divide the monitoring period into several time nodes, and obtain the actual position coordinates of the vehicle corresponding to each time node ( ), connect the actual position coordinates of the vehicle corresponding to each time node to obtain the actual driving path of the vehicle; Based on the actual driving path of the vehicle, the actual driving path of the vehicle is compared with the preset driving path of the vehicle. The comparison process is as follows: The actual position coordinates of the vehicle corresponding to each time node are subtracted from the preset position coordinates of the vehicle to obtain the vehicle position deviation value; The vehicle position deviation values ​​are added and averaged to obtain the vehicle path deviation value.

5. The intelligent monitoring method based on high-speed entrance according to claim 1 is characterized in that: In step 3, the vehicle driving stability value is obtained as follows: During the monitoring period, the number of hasty vehicle driving and the number of vehicle derailment in the merging area are obtained, and the number of hasty vehicle driving and the number of vehicle derailment are added together to obtain the vehicle driving stability value.

6. The intelligent monitoring method based on high-speed entrance according to claim 5 is characterized in that: In step 3, the process of obtaining the number of hasty driving times of the vehicle is as follows: During the monitoring period, the real-time speed of the abnormal merging vehicle is obtained, and an XY axis coordinate system is established. The X axis represents the monitoring time point, and the Y axis represents the speed of the abnormal merging vehicle corresponding to each monitoring time point during the monitoring period. The real-time speed of the abnormal merging vehicle is substituted into the XY axis coordinate system to obtain the real-time speed change curve of the abnormal merging vehicle; Based on the real-time speed change curve of the abnormal merging vehicle, the peak coordinate value in the real-time speed change curve of the abnormal merging vehicle is extracted and marked as ( , ), the trough coordinate value, marked as ( , ); Calculate the distance between the coordinate values ​​of two adjacent wave crests and the coordinate values ​​of wave troughs to obtain the speed change value; The speed change value is compared with the speed change threshold. The comparison process is as follows: If the speed change value is greater than or equal to the speed change threshold, the probability of rush is high, and the time period is marked as a rush time period; The number of times the hasty vehicle time period appears in the real-time speed change curve of the abnormal merging vehicles is obtained, and the number of hasty vehicle driving times is obtained.

7. The intelligent monitoring method based on high-speed entrance according to claim 5 is characterized in that: In step 3, the number of times the vehicle deviates from the track is obtained as follows: Based on the vehicle position deviation value in the above step 2, the vehicle position deviation values ​​in the monitoring period are added and averaged to obtain the vehicle position deviation threshold; The vehicle position deviation value is compared with the vehicle position deviation threshold. The comparison process is as follows: If the vehicle position deviation value is greater than or equal to the vehicle position deviation threshold, the time point at which the position deviation large signal is generated is marked as the position deviation time point; If the vehicle position deviation value is less than the vehicle position deviation threshold, the time period in which the position deviation small signal is generated is marked as a non-position deviation time point; The number of position deviation time points within the monitoring period is obtained to obtain the number of times the vehicle deviates from the track.

8. The intelligent monitoring method based on high-speed entrance according to claim 1 is characterized in that: In step 4, the probability value of an accident occurring in the merging area is obtained in the following way: Obtaining the impact value of the number of abnormal merging vehicles and the impact value of the time of abnormal merging vehicles, adding the impact value of the number of abnormal merging vehicles and the impact value of the time of abnormal merging vehicles to obtain the probability value of an accident occurring in the merging area; The process of obtaining the impact value of the number of abnormal merging vehicles is as follows: During the monitoring period, the vehicle area ratio affected by the abnormal merging vehicle and the area ratio of the abnormal merging vehicle are obtained, and the vehicle area ratio affected by the abnormal merging vehicle and the area ratio of the abnormal merging vehicle are added together to obtain the impact value of the number of abnormal merging vehicles; The process of obtaining the area ratio of abnormal merging vehicles is as follows: During the monitoring period, the area occupied by the abnormal merging vehicle is obtained, and the area occupied by the abnormal merging vehicle is calculated to be a ratio of the area occupied by the abnormal merging vehicle to the area occupied by the vehicle, so as to obtain the abnormal merging vehicle area ratio; The process of obtaining the area ratio of vehicles affected by abnormal merging vehicles is as follows: During the monitoring period, the vehicle area affected by the abnormal merging vehicle is obtained, and the ratio of the vehicle area affected by the abnormal merging vehicle to the area occupied by the vehicle is calculated to obtain the vehicle area ratio affected by the abnormal merging vehicle.

9. The intelligent monitoring method based on high-speed entrance according to claim 8 is characterized in that: In step 4, the time impact value of the abnormal merging vehicle is obtained as follows: During the monitoring period, the length of time for the abnormal merging vehicle to pass and the length of time for the abnormal merging vehicle to affect the vehicle to pass are obtained, and the length of time for the abnormal merging vehicle to pass and the length of time for the abnormal merging vehicle to affect the vehicle to pass are added together to obtain the time impact value of the abnormal merging vehicle; The process of obtaining the length of time for abnormal merging vehicles is as follows: During the monitoring period, the travel time of abnormal merging vehicles in the merging area is obtained, and the travel time of abnormal merging vehicles is added up to obtain the total travel time of abnormal merging vehicles; The total time of abnormal merging vehicles passing is calculated by ratio with the monitoring cycle time to obtain the length of the abnormal merging vehicle passing time; The process of obtaining the length of time that abnormal merging vehicles affect the passage of vehicles is as follows: During the monitoring period, the time that the abnormal merging vehicles affect the passage of vehicles is obtained, and the time that the abnormal merging vehicles affect the passage of vehicles is added up to obtain the total time that the abnormal merging vehicles affect the passage of vehicles; The total time that the abnormal merging vehicle affects the passage of vehicles is calculated by ratio with the monitoring cycle time, so as to obtain the length of time that the abnormal merging vehicle affects the passage of vehicles; The process of determining the vehicles affected by the abnormal merging vehicle is as described above in the process of obtaining the area ratio of the vehicles affected by the abnormal merging vehicle.

10. An intelligent monitoring system based on high-speed entrances, characterized in that: The system is used to execute the method described in any one of claims 1 to 9, and the system includes the following modules: Congestion monitoring module: monitors the merging area before the highway entrance through monitoring equipment, obtains the regional congestion value, compares it with the threshold, and generates a signal whether the area is congested; If the regional congestion value is greater than or equal to the regional congestion threshold, a regional congestion signal is generated; Merging analysis module: Based on the regional congestion signal, the vehicle merging value is obtained, compared with the threshold, and a signal is generated to determine whether the vehicle merging is abnormal; If the vehicle merging value is greater than or equal to the vehicle merging threshold, a vehicle merging abnormality signal is generated, and the vehicle generating the vehicle merging abnormality signal is marked as a merging abnormality vehicle; Stability assessment module: Based on the abnormal vehicle merging signal, obtain the vehicle driving stability value, compare it with the threshold, and generate a signal to determine whether the vehicle is stable; If the vehicle driving stability value is greater than or equal to the vehicle driving stability threshold, a vehicle driving instability signal is generated; Probability prediction module: Based on the unstable vehicle driving signal, the probability value of the accident in the merging area is obtained, compared with the threshold, and the probability signal of the accident is generated; If the probability value of an accident occurring in the merging area is greater than or equal to the threshold value of the probability value of an accident occurring in the merging area, a large signal of the probability of an accident occurring is generated; Optimization and adjustment module: Based on the large signal of accident probability, the merging speed of vehicles is adjusted to obtain the merging speed adjustment value, thus completing the optimization and adjustment of the merging speed of vehicles; In step 5, when a high accident probability signal is generated, the merging driving of the vehicles is adjusted, and the driving speed of the vehicles in the merging area is multiplied by the adjustment coefficient to obtain the merging driving speed adjustment value; The adjustment coefficient is obtained as follows: The vehicle driving stability deviation coefficient and the merging area accident occurrence deviation coefficient are obtained, and the vehicle driving stability deviation coefficient and the merging area accident occurrence deviation coefficient are added together to obtain an adjustment coefficient.

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