Low-delay warning method for sudden dangerous situation of expressway

Abstract

The invention belongs to the technical field of road traffic safety, and provides a low-delay warning method for sudden dangerous situations of an expressway, which comprises the following steps that: an expressway management platform acquires latitude and longitude coordinates of an accident occurrence position; the operator searches all base stations within a specified distance range by taking the latitude and longitude coordinates as a center, and obtains the position information of a user mobile phone accessed to the searched base station; the safety early warning cloud platform divides the risk level of the base station based on the distance between the base station and the accident occurrence position and the type of the base station, obtains a user mobile phone number accessed to the base station based on user mobile phone position information provided by an operator, and sets the user mobile phone number to be the same as the risk level of the accessed base station; and the safety early warning cloud platform sets prompt frequencies corresponding to the risk levels for the user mobile phone numbers according to the risk levels of the user mobile phone numbers, and automatically calls the user mobile phone numbers with different risk levels according to the prompt frequencies through the artificial intelligence customer service to prompt.

Description

Technical Field

[0001] The present invention relates to the technical field of road traffic safety, and in particular to a low-delay warning method for sudden dangerous situations on highways. Background Art

[0002] Road safety is a vital part of the modern transportation system. With the increase in the number of vehicles and the increasing complexity of the transportation network, sudden dangerous situations on the road are becoming more and more frequent. These emergencies may include traffic accidents, natural disasters (such as floods and landslides), road obstacles, etc., which pose a serious threat to the safety of drivers. Traditional road safety warning systems often rely on fixed traffic signs or broadcast information, but these methods have obvious limitations, such as untimely information updates and limited coverage.

[0004] If an accident occurs at night, under severe weather conditions such as heavy rain and floods, the visibility on the highway is low at night, and the vision of drivers and passengers is extremely poor, making it difficult for them to detect the danger ahead in time. Therefore, reducing the notification time of warning information from the highway management platform to the drivers and passengers is a crucial issue. The present invention improves the transmission efficiency of warning information by designing a set of sudden danger warning notification methods, ensuring that a large number of drivers and passengers are notified in a very short time, and can effectively reduce the occurrence of secondary accidents.

[0005] Today's rapid warning solutions for sudden dangerous situations on the road still have defects. Most existing warning methods push danger information to on-board equipment, but most vehicles are not equipped with any related equipment for the Internet of Vehicles. Therefore, when a sudden dangerous situation occurs on the road, it is difficult for nearby drivers and passengers to receive danger warning information in the first time.

[0006] In recent years, with the development of Internet of Things technology, sensor devices have been widely used in road monitoring systems, which can collect road data in real time and identify potential dangerous situations. At the same time, as long as the location coordinates of the sudden dangerous situation are available, the operator can accurately locate the location of nearby vehicles and drivers. In addition, the development of artificial intelligence technology has provided more possibilities for automated customer service. Robot customer service can send customized warning messages to a large number of users by making phone calls or other communication methods.

[0007] Despite the support of the above technologies, there is still a lack of an effective solution to fully integrate existing resources to achieve rapid response to sudden dangerous situations on the road and timely warnings to drivers and passengers. Summary of the invention

[0008] The purpose of the present invention is to provide a low-latency warning method for sudden dangerous situations on highways, which can combine the safety warning method of highway roadside field equipment, mobile operator location data and artificial intelligence customer service, and is of great significance for improving road safety and avoiding secondary injuries caused by traffic accidents. This method can monitor road conditions in real time, accurately identify dangerous situations, and quickly notify nearby drivers and passengers according to priority so that they can take necessary preventive measures.

[0009] The present invention solves the technical problem and adopts the following technical solution: A low-latency warning method for sudden dangerous situations on highways, comprising the following steps: The highway management platform obtains the longitude and latitude coordinates of the accident location and forwards them to the safety warning cloud platform. After receiving the longitude and latitude coordinates of the accident location, the safety warning cloud platform notifies the operator. After receiving the notification from the security warning cloud platform, the operator searches for all base stations within the specified distance range with the longitude and latitude coordinates as the center, obtains the location information of the user's mobile phone connected to the searched base station, and responds to the security warning cloud platform; After receiving the response from the operator, the security warning cloud platform classifies the risk level of the base station based on the distance from the accident location and the base station type, obtains the user's mobile phone number connected to the base station based on the user's mobile phone location information provided by the operator, and sets the user's mobile phone number to the same risk level as the base station; The security warning cloud platform sets reminder frequencies corresponding to the risk levels of users' mobile phone numbers based on their risk levels, and uses artificial intelligence customer service to automatically make phone calls to users' mobile phone numbers at different risk levels according to the reminder frequencies.

[0010] As a further optimization, the highway management platform obtains the latitude and longitude coordinates of the accident location, including: Obtain on-site equipment on the expressway and connect it to the expressway management platform; When an accident occurs on a highway, determine whether the location information of the accident location can be directly obtained through the road site equipment. If so, directly obtain the location information of the accident location through the road site equipment, and determine the longitude and latitude coordinates based on the location information and send them to the highway management platform; Otherwise, the pile number of the accident location is obtained and sent to the highway management platform, which locates the longitude and latitude coordinates of the accident location based on the pile number.

[0011] As a further optimization, the safety warning cloud platform divides the risk level of the base station based on the distance between the base station and the accident location and the base station type, including: When the base stations searched by the operator include 2G base stations or 3G base stations, the security warning cloud platform will set the searched 2G base stations or 3G base stations to high risk levels; When the base stations searched by the operator include 4G base stations or 5G base stations, the safety warning cloud platform will sort the distance difference between the location information of the searched base stations and the longitude and latitude coordinates of the accident location from near to far, and set the base stations with a distance difference within a first preset distance to a high risk level, the base stations with a distance difference between the first preset distance and the second preset distance to a medium risk level, and the base stations with a distance difference greater than the second preset distance to a low risk level.

[0012] As a further optimization, the number of the artificial intelligence customer service is at least K, when the number of mobile phone numbers of users with high, medium and low risk levels is respectively M 1. M 2. M 3, the minimum number of AI customer service calls to high, medium and low risk level user mobile phone numbers K 1. K 2. K 3Should meet:

[0013] The minimum number of AI customer service agents required K Should meet K = K 1+ K 2+ K 3.

[0014] As a further optimization, artificial intelligence customer service will automatically call the mobile phone numbers of users with different risk levels according to the reminder frequency for the first time and then repeat the reminder.

[0015] As a further optimization, the security warning cloud platform completes a reminder based on the time it takes for the artificial intelligence customer service to complete the reminder. t , repeatedly notifying the mobile phone numbers of users with different risk levels at different frequencies; For high-risk user mobile phone numbers, AI customer service will t Make a call once every 1 second. For mobile phone numbers with medium risk levels, AI customer service will make a call every t Make a call every 2 seconds. For low-risk user mobile phone numbers, the AI ​​customer service will t Make a call every 3 seconds, including: .

[0016] As a further optimization, based on the user mobile phone location information provided by the mobile operator, the safety warning cloud platform updates the user mobile phone location information within the specified distance range of the accident location at regular intervals. The update interval is T seconds, after the update, reset the risk level of the user's mobile phone number. For user mobile phone numbers with increased risk levels, T After the update, the AI ​​customer service will call again to provide additional reminders, and the time interval for repeated reminders will be set to the repeated time interval corresponding to the new risk level.

[0017] The beneficial effects of the present invention are: through the above-mentioned low-latency warning method for sudden dangerous situations on highways, the safety warning cloud platform can automatically notify a large number of drivers and passengers in dangerous sections immediately after obtaining the positioning information. The required trigger time is short and the response is rapid. In addition, the present invention does not require the addition of roadside equipment or vehicle-mounted equipment, nor does it require the installation of safety warning applications on the mobile phones of drivers and passengers. Artificial intelligence customer service is used to directly make calls, which lowers the usage threshold and saves operating costs. Finally, the safety warning cloud platform can update the user's mobile phone location information at specific intervals to continuously identify whether there are other vehicles entering the danger range, thereby achieving full coverage of vehicle prompts on roads within the danger range. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of a low-delay warning method for sudden dangerous situations on highways in the implementation of the present invention; Figure 2 A schematic diagram of the classification of base stations in the implementation of the present invention; Figure 3 Schematic diagram of the change in risk level of vehicles of users with different risk levels in the implementation of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations. Example

[0020] This embodiment provides a low-latency warning method for sudden dangerous situations on highways. Figure 1 , wherein the method comprises the following steps: S1. The highway management platform obtains the longitude and latitude coordinates of the accident location and forwards them to the safety warning cloud platform. After the safety warning cloud platform receives the longitude and latitude coordinates of the accident location, it notifies the operator. S2. After receiving the notification from the security warning cloud platform, the operator searches for all base stations within the specified distance range with the longitude and latitude coordinates as the center, obtains the location information of the user's mobile phone connected to the searched base station, and responds to the security warning cloud platform; S3. After receiving the response from the operator, the security warning cloud platform classifies the risk level of the base station based on the distance from the base station to the accident location and the base station type, and obtains the user's mobile phone number connected to the base station based on the user's mobile phone location information provided by the operator, and sets the user's mobile phone number to the same risk level as the base station connected; S4. The security warning cloud platform sets reminder frequencies corresponding to the risk levels of users’ mobile phone numbers according to their risk levels, and uses artificial intelligence customer service to automatically make phone calls to users’ mobile phone numbers at different risk levels according to the reminder frequencies.

[0021] By using the above method of this embodiment, after a dangerous accident occurs, drivers and passengers in the vicinity of the accident can be quickly notified in a short period of time to avoid the occurrence of a secondary accident.

[0022] It should be noted that the accidents mentioned in this embodiment include but are not limited to: road collapse, road deformation, foreign objects on the road, car accidents, etc.

[0023] For existing highways, some accidents can be directly monitored and acquired through on-site equipment on the highway, while others need to be further acquired through the pile number of the highway. Therefore, in this embodiment, the longitude and latitude coordinates of the location where the accident occurred acquired by the highway management platform may include: Obtain on-site equipment on the expressway and connect it to the expressway management platform; When an accident occurs on a highway, determine whether the location information of the accident location can be directly obtained through the road site equipment. If so, directly obtain the location information of the accident location through the road site equipment, and determine the longitude and latitude coordinates based on the location information and send them to the highway management platform; Otherwise, the pile number of the accident location is obtained and sent to the highway management platform, which locates the longitude and latitude coordinates of the accident location based on the pile number.

[0024] Here, the security cloud early warning platform can receive real-time data from operators through the interconnection with the operator's API. The longitude and latitude coordinates can be known in advance in this embodiment. All base stations within the operator's search range can include 2G, 3G, 4G, and 5G base stations. The principle of dividing the risk level of the base station is as follows: all 2G and 3G base stations are classified as high risk levels, and 4G and 5G base stations are classified as high, medium, and low risk levels according to the distance from the accident site. Since the coverage of 2G and 3G base stations is relatively large, they are closer to the accident site. D All 2G and 3G base stations within a kilometer should be classified as high-risk base stations; and the coverage of 4G and 5G base stations is relatively small, so the distance from the accident site should be D 4G and 5G base stations within 1 km are classified as high-risk base stations. D 1- D 4G and 5G base stations within 2 km are classified as medium-risk base stations. D 2- D 4G and 5G base stations within 3 kilometers are classified as low-risk base stations.

[0025] For details, see Figure 2 Suppose a dangerous accident suddenly occurs on the highway. At this time, the cloud warning platform obtains the latitude and longitude coordinates of the dangerous accident through the highway management platform. By connecting to the operator's API, it searches all base stations within 10km of the accident site. After the search, all 2G and 3G base stations are classified as high risk levels, and 4G and 5G base stations are divided into high, medium and low levels according to the range of 0-1km, 1-5km and 5-10km from the accident site.

[0026] Therefore, in this embodiment, the safety warning cloud platform divides the risk level of the base station based on the distance between the base station and the accident location and the base station type, which may include: When the base stations searched by the operator include 2G base stations or 3G base stations, the security warning cloud platform will set the searched 2G base stations or 3G base stations to high risk levels; When the base stations searched by the operator include 4G base stations or 5G base stations, the safety warning cloud platform will sort the distance difference between the location information of the searched base stations and the latitude and longitude coordinates of the accident location from near to far, and set the base stations with a distance difference within the first preset distance to a high risk level, the base stations with a distance difference between the first preset distance and the second preset distance to a medium risk level, and the base stations with a distance difference greater than the second preset distance to a low risk level. The preset distance can be adjusted based on the actual accident situation on the highway.

[0027] When the artificial intelligence customer service makes a phone call reminder, the number of users is generally not a single number. Therefore, the risk level of the user's mobile phone number may also have multiple risk levels. Therefore, in this embodiment, the number of artificial intelligence customer service is at least K. When the number of user mobile phone numbers with high, medium and low risk levels is respectively M 1. M 2. M 3, the minimum number of AI customer service calls to high, medium and low risk level user mobile phone numbers K 1. K 2. K 3Should meet:

[0028] The minimum number of AI customer service agents required K Should meet K = K 1+ K 2+ K 3.

[0029] In order to further ensure user safety, in this embodiment, after the artificial intelligence customer service automatically calls the mobile phone numbers of users with different risk levels according to the reminder frequency for the first time, it is necessary to repeat the reminder.

[0030] In this embodiment, in order to further ensure that the mobile phone numbers of users with different risk levels can be prompted, the security warning cloud platform completes a prompt based on the time of the artificial intelligence customer service. t , it is necessary to repeatedly notify the mobile phone numbers of users with different risk levels at different frequencies; For high-risk user mobile phone numbers, AI customer service will t Make a call once every 1 second. For mobile phone numbers with medium risk levels, AI customer service will make a call every t Make a call every 2 seconds. For low-risk user mobile phone numbers, the AI ​​customer service will t Make a call every 3 seconds, including: .

[0031] Among them, the artificial intelligence customer service is based on the security early warning cloud platform. After receiving the instruction, it can immediately call the mobile phone numbers of all users in the risk area, and notify the users again at a certain time interval. The time interval for calling users varies according to different risk levels. Assuming that the time for the artificial intelligence customer service to call and notify the user is 15s, the time interval for calling the mobile phone numbers of high-risk users is 15s, the time interval for calling the mobile phone numbers of medium-risk users is 30s, and the time interval for calling the mobile phone numbers of low-risk users is 60s.

[0032] Since the vehicles that most users take change dynamically, in order to ensure accurate prompting of all users, in this embodiment, based on the user mobile phone location information provided by the mobile operator, the safety warning cloud platform updates the user mobile phone location information within a specified distance range of the accident location at regular intervals. The update interval is T seconds, after the update, the risk level of the user's mobile phone number is reset. For the user's mobile phone number with an increased risk level, that is, after the update, the user's risk level changes from low risk to medium risk, or from medium risk to high risk, in T After the update, the AI ​​customer service will call again to provide additional reminders, and the time interval for repeated reminders will be set to the repeated time interval corresponding to the new risk level.

[0033] In this embodiment, it is assumed that the time interval for the operator to update the base station and map information is 15s. At this time, the security warning cloud platform is updated every 15s to update the risk level of the user's mobile phone number and the user location information. At the same time, different treatments are performed for users who change risk areas: users who are downgraded from high risk to medium risk, or medium risk to low risk, are changed to the notification interval of the current risk level; users who are upgraded from low risk to medium risk, or medium risk to high risk, are immediately notified by phone and the notification interval is changed to the current risk level.

[0034] See also Figure 3 ,exist t At 0:00, the vehicle access distance to the accident site L 1km away from base station 1, the driver and passengers of the vehicle are judged to be at medium risk, and the AI ​​customer service should make a voice call to remind them and follow the time interval t 2Repeat the prompt. T When the operator updates the location information after s, the vehicle is within the distance of the accident site. L The access range of base station 2 is 2 km, and its risk level becomes high risk. t 0+ T The manual customer service should make a voice call to remind you at the specified time interval. t 1Repeat prompt.

[0035] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A low-latency warning method for sudden dangerous situations on highways, characterized in that: The steps include: The highway management platform obtains the longitude and latitude coordinates of the accident location and forwards them to the safety warning cloud platform. When the safety warning cloud platform receives the longitude and latitude coordinates of the accident location, it notifies the operator; After receiving the notification from the security warning cloud platform, the operator searches for all base stations within the specified distance range with the longitude and latitude coordinates as the center, obtains the location information of the user's mobile phone connected to the searched base station, and responds to the security warning cloud platform; After receiving the response from the operator, the security warning cloud platform classifies the risk level of the base station based on the distance from the accident location and the base station type, and obtains the user's mobile phone number connected to the base station based on the user's mobile phone location information provided by the operator, and sets the user's mobile phone number to the same risk level as the base station. The security warning cloud platform sets reminder frequencies corresponding to the risk levels of users' mobile phone numbers based on their risk levels, and uses artificial intelligence customer service to automatically make phone calls to users' mobile phone numbers at different risk levels according to the reminder frequencies.

2. A low-latency warning method for sudden dangerous situations on highways according to claim 1, characterized in that: The highway management platform obtains the latitude and longitude coordinates of the accident location, including: Obtain on-site equipment on the expressway and connect it to the expressway management platform; When an accident occurs on a highway, determine whether the location information of the accident location can be directly obtained through the road site equipment. If so, directly obtain the location information of the accident location through the road site equipment, and determine the longitude and latitude coordinates based on the location information and send them to the highway management platform; Otherwise, the pile number of the accident location is obtained and sent to the highway management platform, which locates the longitude and latitude coordinates of the accident location based on the pile number.

3. A low-latency warning method for sudden dangerous situations on highways according to claim 1, characterized in that: The safety warning cloud platform divides the risk level of the base station based on the distance between the base station and the accident location and the base station type, including: When the base stations searched by the operator include 2G base stations or 3G base stations, the security warning cloud platform will set the searched 2G base stations or 3G base stations to high risk levels; When the base stations searched by the operator include 4G base stations or 5G base stations, the safety warning cloud platform will sort the distance difference between the location information of the searched base stations and the longitude and latitude coordinates of the accident location from near to far, and set the base stations with a distance difference within a first preset distance to a high risk level, the base stations with a distance difference between the first preset distance and the second preset distance to a medium risk level, and the base stations with a distance difference greater than the second preset distance to a low risk level.

4. A low-latency warning method for sudden dangerous situations on highways according to claim 3, characterized in that: The number of the artificial intelligence customer service is at least K, and when the number of mobile phone numbers of users with high, medium and low risk levels is respectively M 1. M 2. M 3, the minimum number of AI customer service calls to high, medium and low risk level user mobile phone numbers K 1. K 2. K 3Should meet: ， The minimum number of AI customer service agents required K Should meet K = K 1+ K 2+ K 3.

5. A low-latency warning method for sudden dangerous situations on highways according to claim 3, characterized in that: After the artificial intelligence customer service automatically calls the mobile phone numbers of users with different risk levels according to the reminder frequency for the first time, repeated reminders will be made.

6. A low-latency warning method for sudden dangerous situations on highways according to claim 5, characterized in that: The security warning cloud platform completes a reminder based on the time t , repeatedly notifying the mobile phone numbers of users with different risk levels at different frequencies; For high-risk user mobile phone numbers, AI customer service will t Make a call once every 1 second. For mobile phone numbers with medium risk levels, AI customer service will make a call every t Make a call every 2 seconds. For low-risk user mobile phone numbers, the AI ​​customer service will t Make a call every 3 seconds, including: 。 7. A low-latency warning method for sudden dangerous situations on highways according to claim 1, characterized in that: Based on the user's mobile phone location information provided by the mobile operator, the safety warning cloud platform updates the user's mobile phone location information within the specified distance range of the accident location at regular intervals. The update interval is T seconds, after the update, reset the risk level of the user's mobile phone number. For user mobile phone numbers with increased risk levels, T After the update, the AI ​​customer service will call again to provide additional reminders, and the time interval for repeated reminders will be set to the repeated time interval corresponding to the new risk level.

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