Method, device, equipment and storage medium for identifying accident-prone areas

Abstract

The present application discloses a method, device, equipment and storage medium for identifying accident-prone areas, which relates to the field of data processing technology and is used to improve the rationality and accuracy of accident-prone area identification. The method includes: obtaining the absolute position information of multiple accident points included in the target road; sorting the multiple accident points according to the absolute position information of the multiple accident points to obtain an accident point sequence; determining the current accident section corresponding to the current accident point in the accident point sequence; when the current accident section is an accident-prone area, updating the next accident point of the current accident section in the accident point sequence as the current accident point, until the updated current accident point is the last accident point in the accident point sequence; when the current accident section is not an accident-prone area, updating the next accident point of the current accident point in the accident point sequence as the current accident point, until the updated accident point is the last accident point in the accident point sequence.

Description

Technical Field

[0001] The present application relates to the field of traffic safety technology, and in particular to a method, device, equipment and storage medium for identifying accident-prone areas. Background Art

[0002] At present, in order to reduce road safety risks, it is usually necessary to identify accident-prone areas so that subsequent processing can be more targeted to reduce the occurrence of traffic accidents and improve road safety. In related technologies, data mining methods are usually used to integrate multivariate statistics, spatial analysis, clustering algorithms and other algorithmic ideas to achieve the identification of accident-prone areas.

[0003] However, in the above methods, data mining has high requirements for the accuracy of accident location data. The current accident location data is mainly recorded manually by managers based on the name of the road where the accident occurred, the number of kilometers, the distance and other information, and then processed through geographic information data such as map data and mileage pile data. The location data is converted into longitude and latitude before subsequent data clustering and other operations can be performed. When the longitude and latitude data of the accident are biased, it will lead to misjudgment of accident-prone areas, which will in turn affect the judgment of road risks. Therefore, the current identification of accident-prone areas is less reasonable and less accurate. Summary of the invention

[0004] The present application provides a method, device, equipment and storage medium for identifying accident-prone areas, which are used to improve the rationality and accuracy of accident-prone area identification.

[0005] In order to achieve the above objectives, this application adopts the following technical solutions:

[0006] In a first aspect, a method for identifying accident-prone areas is provided, the method comprising: acquiring absolute position information of a plurality of accident points included in a target road; sorting the plurality of accident points according to the absolute position information of the plurality of accident points to obtain an accident point sequence; determining a current accident section corresponding to a current accident point in the accident point sequence; the current accident section comprising the current accident point, and an accident point in the accident point sequence that is located after the current accident point and whose distance from the current accident point is less than or equal to a first distance; when the current accident section is an accident-prone area, updating the next accident point of the current accident section in the accident point sequence to the current accident point, until the updated current accident point is the last accident point in the accident point sequence; when the current accident section is not an accident-prone area, updating the next accident point of the current accident point in the accident point sequence to the current accident point, until the updated accident point is the last accident point in the accident point sequence.

[0007] In one design, the method also includes: when the number of target accident points in the current accident section meets the casualty condition, determining that the accident points in the current accident section meet the first condition; the target accident point is an accident point whose casualty information meets the casualty condition within a preset time period; when the number of target accident points in the current accident section meets the casualty condition, if the distance between the target accident point and any static indicator is less than or equal to the second distance, determining that the accident points in the current accident section meet the second condition; determining the ratio of the number of accident points in the current accident section to the length of the current accident section as the number of accident points per unit length of the current accident section; when the number of accident points per unit length of the current accident section is greater than or equal to a preset threshold, determining that the accident points in the current accident section meet the third condition; when the accident points in the current accident section meet any one of the first condition, the second condition and the third condition, determining that the current accident section is an accident-prone area; when the current accident section does not meet the first condition, the second condition and the third condition, determining that the current accident section is not an accident-prone area.

[0008] In one design, the method also includes: for a first accident-prone area in a target road, determining a plurality of first target static indicators in the target road whose distance from the first accident-prone area is less than or equal to a third distance; the first accident-prone area is any one of the accident-prone areas in the target road; the types of the plurality of first target static indicators are different, and each of the plurality of first target static indicators is a static indicator of the same type that is closest to the first accident-prone area; determining a distance risk value for each first target static indicator to obtain distance risk values ​​for a plurality of first target static indicators; the distance risk value is used to indicate the degree of risk impact of each first target static indicator on the first accident-prone area; generating a static indicator risk assessment result for the first accident-prone area based on the distance risk values ​​of the plurality of first target static indicators; the static indicator risk assessment result is used to indicate the result after ranking the degree of risk impact of different first target static indicators on the first accident-prone area.

[0009] In one design, determining the distance risk value of each first target static indicator includes: obtaining the distance between each first target static indicator and the first accident-prone place, and obtaining a distance risk calculation rule for each first target static indicator; the distance risk calculation rule corresponds to the distance risk relationship of the static indicator one-to-one, and the distance risk relationship is used to indicate the degree of danger corresponding to positions at different distances from the static indicator; determining the distance risk value of each first target static indicator based on the distance between each first target static indicator and the first accident-prone place, and the distance risk calculation rule for each first target static indicator.

[0010] In one design, the method also includes: obtaining accident point distribution data of a first type of static indicator in a target road; the first type of static indicator is any type of static indicator in the target road; the accident point distribution data includes the distance between each static indicator and the corresponding accident point under the first type of static indicator and the number of corresponding accident points; the distance between each static indicator and the corresponding accident point is less than or equal to a fourth distance, and each static indicator is the static indicator of the first type of static indicator that is closest to the corresponding accident point; based on the accident point distribution data, determining the distance risk relationship of the first type of static indicator.

[0011] In one design, a static indicator risk assessment result of a first accident-prone area is generated based on the distance risk values ​​of multiple first target static indicators, including: determining the product of the weight corresponding to the type of each first target static indicator and the distance risk value of each first target static indicator to obtain multiple products; and sorting the multiple products to obtain a static indicator risk assessment result.

[0012] In one design, the method also includes: obtaining the number of accident points corresponding to each static indicator under the first type of static indicators, and the length of each static indicator; the first type of static indicators are any type of static indicators in the target road; the distance between each static indicator and the corresponding accident point is less than or equal to the fifth distance, and each static indicator is the static indicator of the first type of static indicators that is closest to the corresponding accident point; the ratio of the sum of the number of accident points corresponding to all static indicators under the first type of static indicators to the sum of the lengths of all static indicators is determined as the weight of the first type of static indicators.

[0013] In one design, the method also includes: obtaining the number of accident points corresponding to each static indicator under the first type of static indicators, and the length of each static indicator; the first type of static indicators are any type of static indicators in the target road; the distance between each static indicator and the corresponding accident point is less than or equal to the fifth distance, and each static indicator is the static indicator of the first type of static indicators that is closest to the corresponding accident point; the ratio of the sum of the number of accident points corresponding to all static indicators under the first type of static indicators to the sum of the lengths of all static indicators is determined as the first ratio of the first type of static indicators, and the first ratio of all types of static indicators is obtained; the ratio of the first ratio of the first type of static indicators to the sum of the first ratios of all types of static indicators is determined as the weight of the first type of static indicators.

[0014] In a second aspect, a device for identifying accident-prone areas is provided, the device comprising: an acquisition unit, a processing unit, and a determination unit; the acquisition unit is used to acquire absolute position information of multiple accident points included in a target road; the processing unit is used to sort the multiple accident points according to the absolute position information of the multiple accident points to obtain an accident point sequence; the determination unit is used to determine a current accident section corresponding to a current accident point in the accident point sequence; the current accident section includes the current accident point, and an accident point in the accident point sequence that is located after the current accident point and whose distance from the current accident point is less than or equal to a first distance; the processing unit is used to, if the current accident section is an accident-prone area, update the next accident point of the current accident section in the accident point sequence to the current accident point, until the updated current accident point is the last accident point in the accident point sequence; if the current accident section is not an accident-prone area, update the next accident point of the current accident point in the accident point sequence to the current accident point, until the updated accident point is the last accident point in the accident point sequence.

[0015] In one design, a determination unit is used to determine that the current accident section is an accident-prone area if the accident points in the current accident section meet any one of the first condition, the second condition and the third condition; the first condition is used to indicate the number of accident points whose casualties meet the casualty condition within a preset time period; the second condition is used to indicate the number of accident points whose casualties meet the casualty condition within a preset time period, and the accidents at the accident points are related to road factors; the third condition is used to indicate the number of accident points in the current accident section; the determination unit is used to determine that the current accident section is not an accident-prone area if the current accident section does not meet the first condition, the second condition and the third condition.

[0016] In one design, a determination unit is used to determine that the accident points of the current accident section meet the first condition when the number of target accident points in the current accident section meets the casualty condition; the target accident point is an accident point whose casualty information meets the casualty condition within a preset time period; the determination unit is used to determine that the accident points of the current accident section meet the second condition when the number of target accident points in the current accident section meets the casualty condition, if the distance between the target accident point and any static indicator is less than or equal to the second distance; the determination unit is used to determine the ratio of the number of accident points in the current accident section to the length of the current accident section as the number of accident points per unit length of the current accident section; the determination unit is used to determine that the accident points of the current accident section meet the third condition when the number of accident points per unit length of the current accident section is greater than or equal to a preset threshold.

[0017] In one design, a determination unit is used to determine, for a first accident-prone area in a target road, a plurality of first target static indicators whose distance from the first accident-prone area is less than or equal to a third distance; the first accident-prone area is any accident-prone area in the target road; the plurality of first target static indicators are of different types, and each of the plurality of first target static indicators is a static indicator of the same type that is closest to the first accident-prone area; the determination unit is used to determine a distance risk value of each first target static indicator to obtain distance risk values ​​of the plurality of first target static indicators; the distance risk value is used to indicate a degree of risk impact of each first target static indicator on the first accident-prone area; the processing unit is used to generate a static indicator risk assessment result of the first accident-prone area according to the distance risk values ​​of the plurality of first target static indicators; the static indicator risk assessment result is used to indicate a result after ranking the degree of risk impact of different first target static indicators on the first accident-prone area.

[0018] In one design, an acquisition unit is used to acquire the distance between each first target static indicator and the first accident-prone area, and to acquire a distance risk calculation rule for each first target static indicator; the distance risk calculation rule corresponds to the distance risk relationship of the static indicator one-to-one, and the distance risk relationship is used to indicate the degree of danger corresponding to positions at different distances from the static indicator; a determination unit is used to determine the distance risk value of each first target static indicator based on the distance between each first target static indicator and the first accident-prone area, and the distance risk calculation rule for each first target static indicator.

[0019] In one design, an acquisition unit is used to acquire accident point distribution data of a first type of static indicator in a target road; the first type of static indicator is any type of static indicator in the target road; the accident point distribution data includes the distance between each static indicator and the corresponding accident point under the first type of static indicator and the number of corresponding accident points; the distance between each static indicator and the corresponding accident point is less than or equal to a fourth distance, and each static indicator is the static indicator of the first type of static indicator that is closest to the corresponding accident point; and a determination unit is used to determine the distance risk relationship of the first type of static indicator based on the accident point distribution data.

[0020] In one design, a determination unit is used to determine the product of a weight corresponding to the type of each first target static indicator and a risk value of the distance of each first target static indicator to obtain multiple products; and a processing unit is used to sort the multiple products to obtain a static indicator risk assessment result.

[0021] In one design, an acquisition unit is used to obtain the number of accident points corresponding to each static indicator under a first type of static indicator, and the length of each static indicator; the first type of static indicator is any type of static indicator in the target road; the distance between each static indicator and the corresponding accident point is less than or equal to the fifth distance, and each static indicator is the static indicator of the first type of static indicator that is closest to the corresponding accident point; and a determination unit is used to determine the weight of the first type of static indicator as the ratio of the sum of the number of accident points corresponding to all static indicators under the first type of static indicator to the sum of the lengths of all static indicators.

[0022] In one design, an acquisition unit is used to obtain the number of accident points corresponding to each static indicator under a first type of static indicator, and the length of each static indicator; the first type of static indicator is any type of static indicator in the target road; the distance between each static indicator and the corresponding accident point is less than or equal to the fifth distance, and each static indicator is the static indicator of the first type of static indicator closest to the corresponding accident point; the determination unit is used to determine the ratio of the sum of the number of accident points corresponding to all static indicators under the first type of static indicators to the sum of the lengths of all static indicators as a first ratio of the first type of static indicators, and obtain the first ratio of all types of static indicators; the determination unit is used to determine the ratio of the first ratio of the first type of static indicator to the sum of the first ratios of all types of static indicators as the weight of the first type of static indicator.

[0023] In a third aspect, an electronic device is provided, comprising: a processor and a memory; wherein the memory is used to store one or more programs, and the one or more programs include computer execution instructions. When the electronic device is running, the processor executes the computer execution instructions stored in the memory to enable the electronic device to perform an accident-prone area identification method as in the first aspect.

[0024] In a fourth aspect, a computer-readable storage medium storing one or more programs is provided. The one or more programs include instructions, and when the instructions are executed by a computer, the computer executes a method for identifying accident-prone areas as described in the first aspect.

[0025] In a fifth aspect, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the accident-prone area identification method of the first aspect.

[0026] The present application provides a method, device, equipment and storage medium for identifying accident-prone areas, which are applied to the scene of identifying accident-prone areas on roads. First, the absolute position information of multiple accident points included in the target road is obtained, and the multiple accident points are sorted according to the absolute position information of the multiple accident points to obtain an accident point sequence; further, by determining the current accident section corresponding to the current accident point in the accident point sequence, including the current accident point and the accident points in the accident point sequence that are located after the current accident point and whose distance from the current accident point is less than or equal to the first distance, if the current accident section is an accident-prone area, the next accident point of the current accident section in the accident point sequence is updated to the current accident point, until the updated current accident point is the last accident point in the accident point sequence; and if the current accident section is not an accident-prone area, the next accident point of the current accident point in the accident point sequence is updated to the current accident point, until the updated accident point is the last accident point in the accident point sequence. Through the above method, the accident section is determined based on the absolute position information of the accident point and the first distance, and then by judging the accident section, it is identified whether the accident section is an accident-prone area, so as to segment the accident point based on the absolute position information of the accident point, and then complete the judgment and identification of the accident-prone area, thereby improving the rationality and accuracy of the identification of the accident-prone area. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A schematic diagram of the structure of an accident-prone area identification system provided in an embodiment of the present application;

[0028] Figure 2 A schematic diagram of a method for identifying accident-prone areas provided in an embodiment of the present application Figure 1 ;

[0029] Figure 3 A schematic diagram of a method for identifying accident-prone areas provided in an embodiment of the present application Figure 2 ;

[0030] Figure 4 A schematic diagram of a method for identifying accident-prone areas provided in an embodiment of the present application Figure 3 ;

[0031] Figure 5 A schematic diagram of a method for identifying accident-prone areas provided in an embodiment of the present application Figure 4 ;

[0032] Figure 6 A schematic diagram of a method for identifying accident-prone areas provided in an embodiment of the present application Figure 5 ;

[0033] Figure 7A schematic diagram of a method for identifying accident-prone areas provided in an embodiment of the present application Figure 6 ;

[0034] Figure 8 A schematic diagram of a method for identifying accident-prone areas provided in an embodiment of the present application Figure 7 ;

[0035] Fig. 9 A schematic diagram of a method for identifying accident-prone areas provided in an embodiment of the present application Figure 8 ;

[0036] Fig.10 A schematic diagram of a method for identifying accident-prone areas provided in an embodiment of the present application Figure 9 ;

[0037] Fig.11 A schematic diagram of a method for identifying accident-prone areas provided in an embodiment of the present application Figure 10 ;

[0038] Fig.12 A schematic diagram of a method for identifying accident-prone areas provided in an embodiment of the present application Figure 10 one;

[0039] Fig.13 A schematic diagram of a method for identifying accident-prone areas provided in an embodiment of the present application Figure 10 two;

[0040] Fig.14 A schematic diagram of the structure of an accident-prone area identification device provided in an embodiment of the present application;

[0041] Fig.15 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0043] In the description of this application, unless otherwise specified, " / " means "or", for example, A / B can mean A or B. "And / or" in this article is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, "at least one" and "plurality" refer to two or more. The words "first", "second", etc. do not limit the quantity and execution order, and the words "first", "second", etc. do not limit them to be different.

[0044] At present, in the related technologies, the identification of accident-prone areas is mainly carried out by analyzing historical accident information through data mining algorithms to determine accident-prone areas. The current data mining method usually refers to a clustering algorithm, which refers to clustering the road sections where accident-prone points are concentrated in space into accident clusters through related algorithms (such as fuzzy clustering, k-means algorithm, DBSCAN algorithm, etc.), and then determining the road sections where the accident clusters are located as accident-prone areas. However, in the related technologies, the accident location data is mainly recorded manually by management personnel (such as police officers) based on the road number (road number), kilometers, and meters where the accident occurred. For these accident location data, when using clustering algorithms, it is usually necessary to process geographic information data such as map data and mileage post data, and convert information such as road name, kilometers, meters, etc. into latitude and longitude information before subsequent clustering can be performed.

[0045] In the above method, if the latitude and longitude information of the accident is inaccurate (such as deviation, error and interference information, etc.), it will lead to the accuracy of the subsequent spatial clustering results, and thus affect the accuracy of the identification of accident-prone areas. In addition, the accident-prone areas identified in the clustering algorithm pay more attention to the consideration of the number of accidents, while in relevant technologies and relevant specifications, the definition standards for accident-prone areas are more inclined to the severity of different accidents. Therefore, the rationality of the results of accident-prone areas is also poor.

[0046] An accident-prone area identification method provided in an embodiment of the present application can be applied to an accident-prone area identification system. Figure 1 FIG. 2 shows a schematic diagram of the structure of the accident-prone area identification system. Figure 1 As shown, the accident-prone area identification system 20 includes: an electronic device 21 and a server 22. The electronic device 21 is connected to the server 22.

[0047] The accident-prone area identification system 20 can be used in the Internet of Things. The accident-prone area identification system 20 can include hardware such as multiple central processing units (CPUs), multiple memories, and storage devices storing multiple operating systems.

[0048] The electronic device 21 is used to implement data processing. For example, the electronic device 21 can obtain an accident point sequence based on the absolute position information of multiple accident points included in the target road, and then determine the current accident section corresponding to the current accident point in the accident point sequence.

[0049] Optionally, the electronic device 21 is also used to determine whether the current accident section is an accident-prone area.

[0050] The server 22 may be a server corresponding to the accident point, and is used to store data. For example, the server 22 may store the absolute position information of all accident points included in the target road (or preset area), and send the absolute position information to the electronic device 21, so that the electronic device 21 can process the data.

[0051] A method for identifying accident-prone areas provided in an embodiment of the present application is described below in conjunction with the accompanying drawings.

[0052] like Figure 2 As shown, an accident-prone area identification method provided in an embodiment of the present application includes S201-S204:

[0053] S201. Obtain absolute position information of multiple accident points included in the target road.

[0054] Optionally, the target road may be a road within a preset area, such as a road in Province A.

[0055] Optionally, multiple accident points included in the target road may be determined based on a road identification corresponding to each accident point (such as a road number corresponding to each accident point).

[0056] Optionally, the absolute position information of each accident point may be kilometers + meters corresponding to the accident point.

[0057] It should be noted that the absolute position can be understood as the position of the accident point relative to a certain reference point (such as the starting point of the road, the end point of the road, a landmark point outside the road, etc.).

[0058] Optionally, the absolute position information of each accident point can be determined based on the accident information of each accident point.

[0059] It should be noted that the accident information of each accident point may include the road name (road name), kilometres, meters, absolute location information (kilometres + meters), number of injured persons, number of deaths and other information corresponding to the accident.

[0060] S202. Sort the multiple accident points according to their absolute position information to obtain an accident point sequence.

[0061] Optionally, based on the absolute position information of each of the multiple accident points, the multiple accident points may be sorted according to the size of the absolute position, so as to obtain an accident point sequence.

[0062] Exemplarily, the accident point sequence can be obtained by sorting the accident points in ascending order according to the absolute position information of each accident point among the multiple accident points.

[0063] S203: Determine the current accident section corresponding to the current accident point in the accident point sequence.

[0064] The current accident section includes the current accident point and an accident point in the accident point sequence that is located after the current accident point and whose distance to the current accident point is less than or equal to the first distance.

[0065] Optionally, the absolute position of the current accident point and the absolute position of the current accident point + the first distance may be used as conditions for screening to determine the accident point whose absolute position is between the absolute position of the current accident point and the absolute position of the current accident point + the first distance, thereby determining the current accident section corresponding to the current accident point.

[0066] Exemplarily, all accident points in the accident point sequence can be traversed, and the currently traversed accident point can be defined as the current accident point. The absolute position of the current accident point is d, and all accident points whose absolute positions in this i part of the accident point sequence are greater than d and less than d + the first distance are selected, and these accident points are located as accident points in the current accident segment corresponding to the current accident point.

[0067] Optionally, the first distance may be determined according to specific business requirements.

[0068] Exemplarily, the first distance may be 4000 meters, 3000 meters, or 2000 meters.

[0069] Specifically, taking the first distance of 4000 meters as an example, the absolute position information of all accident points in the accident point sequence can be traversed, and then the accident point whose absolute position is after the absolute position d of the current accident point and before d+4000 meters is determined as the accident point of the current accident section.

[0070] Optionally, different first distances may be determined according to different road types of the target road.

[0071] Exemplarily, road types may include special roads and ordinary roads. Special roads may be expressways and first-class roads, and ordinary roads may be roads other than expressways and first-class roads. For special roads, the corresponding first distance may be 4,000 meters, and for ordinary roads, the corresponding distance may be 2,000 meters.

[0072] Optionally, the accident information of each accident point may further include a road type, and then the road type of the target road is determined according to the accident information of the accident point.

[0073] Optionally, a correspondence table between road numbers (road numbers) and road types may be provided, and then the road type corresponding to the target road may be determined directly according to the road number of the target road.

[0074] S204. When the current accident section is an accident-prone area, the next accident point of the current accident section in the accident point sequence is updated as the current accident point, until the updated current accident point is the last accident point in the accident point sequence; when the current accident section is not an accident-prone area, the next accident point of the current accident point in the accident point sequence is updated as the current accident point, until the updated accident point is the last accident point in the accident point sequence.

[0075] Exemplarily, for the accident point sequence [a1, a2, a3, a4, a5, a6, a7, a8], for the current accident point a1, the current accident section corresponding to the current accident point a1 is determined to be [a1, a2, a3, a4] based on the first distance; when the current accident section is an accident-prone area, a5 is updated to the current accident point until the updated current accident point is a8; when the current accident section is not an accident-prone area, a2 is updated to the current accident point until the updated current accident point is a8.

[0076] Optionally, until the updated current accident point is the last accident point in the accident point sequence, it can be understood that when the updated current accident point is the last accident point in the accident point sequence, after determining whether the current accident section corresponding to the updated current accident point is an accident-prone area, the current accident point will no longer be updated.

[0077] In an embodiment of the present application, first, absolute position information of multiple accident points included in the target road is obtained, and according to the absolute position information of the multiple accident points, the multiple accident points are sorted to obtain an accident point sequence; further, by determining the current accident section corresponding to the current accident point in the accident point sequence, including the current accident point and the accident points in the accident point sequence that are located after the current accident point and whose distance from the current accident point is less than or equal to the first distance, if the current accident section is an accident-prone area, the next accident point of the current accident section in the accident point sequence is updated to the current accident point, until the updated current accident point is the last accident point in the accident point sequence; and if the current accident section is not an accident-prone area, the next accident point of the current accident point in the accident point sequence is updated to the current accident point, until the updated accident point is the last accident point in the accident point sequence. Through the above method, the accident section is determined based on the absolute position information of the accident point and the first distance, and then by judging the accident section, it is identified whether the accident section is an accident-prone area, so as to segment the accident point based on the absolute position information of the accident point, and then complete the judgment and identification of the accident-prone area, thereby improving the rationality and accuracy of the identification of the accident-prone area.

[0078] In one design, Figure 3As shown, in an accident-prone area identification method provided in an embodiment of the present application, the method further includes S301-S302:

[0079] S301. When the accident point of the current accident section satisfies any one of the first condition, the second condition and the third condition, determine that the current accident section is an accident-prone area.

[0080] Among them, the first condition is used to indicate the number of accident points whose casualties meet the casualty conditions within a preset time period; the second condition is used to indicate the number of accident points whose casualties meet the casualty conditions within a preset time period, and the accidents at the accident points are related to road factors; the third condition is used to indicate the number of accident points in the current accident section.

[0081] Optionally, the first condition, the second condition and the third condition may be determined according to business requirements and relevant industry specifications.

[0082] For example, the first, second and third conditions can be determined based on the definition and classification basis of accident-prone areas specified in the "Specifications for the Inspection of Highway Traffic Accident-prone Points and Sections and Serious Safety Hazards (Trial)" stipulated by the relevant traffic management department.

[0083] Optionally, the preset time period can be determined based on business needs and relevant industry specifications.

[0084] Exemplarily, the preset time period may be within 3 years, within 4 years, within 5 years, etc.

[0085] Optionally, the accident information of each accident point may also include the recording time of the accident point (or the generation time of the accident point, or the accident occurrence time corresponding to the accident point), and then determine the accident point within a preset time period through the accident information of each accident point.

[0086] Optionally, when acquiring the absolute position information of multiple accident points included in the target road, the absolute position information of multiple accident points included in the target road within a preset time period may be directly acquired based on the accident information of each accident point.

[0087] It should be noted that the casualties within the preset time period may be the number of injured persons and the number of deaths corresponding to the accident points within the preset time period.

[0088] Optionally, accident-prone areas include accident-prone points and accident-prone sections. When the current accident section is determined to be an accident-prone area, it can be further determined whether the current accident section belongs to an accident-prone point or an accident-prone section based on the accident point information in the current accident section.

[0089] Optionally, when it is determined that the accident section at that time is an accident-prone area, the total length of the current accident section (the distance between the accident point with the largest absolute position and the accident point with the smallest absolute position) can be used. When the total length meets the length requirement of the accident-prone area, it can be determined that the current accident section belongs to the accident-prone area; when the total length does not meet the length requirement of the accident-prone area, it can be determined that the current accident section belongs to the accident-prone area.

[0090] Optionally, the length requirement for accident-prone points can be determined based on specific business needs and relevant industry standards.

[0091] For example, the length requirement for accident-prone spots may be that the total length of the accident section is less than 1000 meters, the total length of the accident section is less than 700 meters, etc.

[0092] Optionally, different road types may have different length requirements for corresponding accident-prone points.

[0093] For example, when the road type is expressway or first-class highway, the length requirement of the corresponding accident-prone points may be less than 1,000 meters; when the road type is ordinary highway, the length requirement of the corresponding accident-prone points may be less than 500 meters.

[0094] S302: When the current accident section does not satisfy the first condition, the second condition, and the third condition, it is determined that the current accident section is not an accident-prone area.

[0095] Optionally, when the current accident section does not meet the first condition, the second condition and the third condition, it can be considered that the current accident section does not meet the definition of an accident-prone area in relevant regulations, thereby determining the current accident section as an accident-prone area.

[0096] Optionally, in combination with the above S203 and S204, by traversing the accident point sequence acds, the currently traversed accident point can be defined as acd, the absolute position as d, and all accident points in acds whose absolute positions are greater than d and less than d+line_threshold (first distance) are selected, and these accident points are defined as list_acd (current accident section), and it is determined whether the accident points in list_acd meet the first condition, the second condition, and the third condition.

[0097] Furthermore, when the accident points in list_acd satisfy any one of the first, second and third conditions, list_acd is determined to be an accident-prone area, and the next accident point after list_acd is updated to the current accident point acd, and traversal is performed again until the traversal of the accident points in acds is completed; when the accident points in list_acd do not satisfy the first, second and third conditions, list_acd is determined not to be an accident-prone area, and the next accident point after acd is updated to the current accident point, and traversal is performed again until the traversal of the accident points in acds is completed.

[0098] Optionally, during the traversal process, when it is determined that list_acd is an accident-prone area, list_acd can be deleted from acds, that is, all accident points in list_acd are deleted from acds; when it is determined that list_acd is not an accident-prone area, acd can be deleted from acds.

[0099] Optionally, before traversal, the acquired accident points can be grouped. First, they are grouped according to the road number to obtain the accident points included in the target road. Then, they are grouped again according to the road type of the accident information. The accident points included in the target road are divided into two types: expressways and first-class highways, and ordinary roads. After the grouping, the accident points are sorted from small to large according to their absolute position.

[0100] Furthermore, the road type of the current group is determined. If the road type belongs to expressway and first-class highway, the accident-prone point length threshold point_threshold is defined as 1000 meters, and the accident-prone section length threshold line_threshold is defined as 4000 meters; if the road type belongs to ordinary highway, the accident-prone point length threshold point_threshold is defined as 500 meters, and the accident-prone section length threshold line_threshold is defined as 2000 meters.

[0101] When it is determined that list_acd is an accident-prone area, the accident point with the smallest absolute position and the accident with the largest absolute position in list_acd can be further used as the starting and ending points to calculate the length of list_acd. If the length is greater than point_threshold, the section where list_acd is located is defined as an accident-prone section, otherwise it is an accident-prone point.

[0102] In the embodiment of the present application, by setting the first condition, the second condition, and the third condition, it is determined from three dimensions whether the current accident section belongs to an accident-prone area, so as to comprehensively consider the situation of the accident point in the current accident section and improve the accuracy and rationality of the identification of accident-prone areas.

[0103] In one design, Figure 4 As shown, the accident-prone area identification method provided in the embodiment of the present application further includes S401-S404:

[0104] S401. When the number of target accident points in the current accident section meets the casualty condition, determine whether the accident points in the current accident section meet the first condition.

[0105] Among them, the target accident point is the accident point where the casualty information meets the casualty conditions within a preset time period.

[0106] Optionally, the casualty condition of the number of target accident points corresponding to the specific first condition and the casualty condition of the casualty information can be determined according to business requirements and relevant industry standards.

[0107] Exemplarily, the first condition may be that the number of target accident points where three or more people die at one time is greater than or equal to 2, the number of target accident points where deaths occur is greater than 6, and so on.

[0108] S402: When the number of target accident points in the current accident section meets the casualty condition, if the distance between the target accident point and any static index is less than or equal to the second distance, it is determined that the accident points in the current accident section meet the second condition.

[0109] Optionally, when the distance between the target accident point and any static index is less than or equal to a second distance, it can be considered that the generation of the accident point (the occurrence of the accident) is related to road factors.

[0110] Optionally, for static indicators, they can be determined based on business needs and relevant industry standards.

[0111] For example, relevant road risk indicators can be determined by combining relevant highway standards (such as "Highway Route Design Specifications (JTGD20-2017)"), traffic safety standards (such as "Technical Specifications for Traffic Management Weather Risk Warning Indicators") and other relevant industry standards with geographic information data such as road static structure and road attributes in technical map data to obtain static indicators.

[0112] Specifically, the static index may be the road static risk index shown in Table 1 and Table 2.

[0113] Optional, such as Figure 5 As shown, the road static risk index can be generated based on traffic information data such as basic road network data table (R table), basic road network data table (N table), basic road network data table (ADAS table), road condition data, trajectory data, water area data and sign data.

[0114] Specifically, Figure 5As shown, based on the R table, LINK attributes can be extracted, based on the N table, NODE attributes can be extracted, and based on the R table and the N table, topological structure information can be extracted, based on the ADAS table, shape point attributes can be extracted, and based on the road condition data and trajectory data, attribute information such as instantaneous speed, average speed and congestion status can be extracted.

[0115] Furthermore, based on the LINK attributes, static indicators such as bridges and tunnels are identified and generated; based on the LINK attributes, topological structure and NODE attributes, static indicators such as ramp main road mismatch points, speed limit change points, lane change points, and sections with too short length in the weaving area are identified and generated; based on the topological structure and shape point attributes, static indicators such as sharp turns, steep slopes, long uphill slopes, long downhill slopes, and long straight lines are identified and generated; based on the topological structure and instantaneous speed, average speed and congestion status, static indicators such as sections with frequent congestion, sections prone to sudden acceleration, and sections prone to sudden deceleration are identified and generated; based on water area data, static indicators such as sections near water are identified and generated; based on sign and signboard data, static indicators such as sections near cliffs are identified and generated.

[0116] It should be noted that for R table data, it refers to the basic road network data table stored in the form of LINK, such as road attribute information, road length information, number of lanes information, speed limit value information, etc.; for N table data, it refers to the basic road network data table stored in the form of NODE, such as road intersection attribute information, etc., and for ADAS table data, it refers to the basic road network data table stored in the form of LINK shape points, such as road curvature information, road slope information, etc. Among them, LINK refers to the smallest digital unit that makes up the road, NODE refers to the endpoints at both ends of LINK, and shape point refers to the point where two straight lines intersect inside LINK.

[0117] Table 1

[0118]

[0119] Table 2

[0120]

[0121] Optionally, the second distance may be determined in combination with specific business requirements and relevant industry standards.

[0122] For example, after many experiments and data statistics, it is found that when the second distance is 1000 meters, the static indicators within this range are strongly correlated with accident-prone areas, and the second distance can be determined to be 1000 meters.

[0123] Optionally, the second distance may also be 900 meters, 800 meters, etc.

[0124] Optionally, for the target accident point, a fixed distance linear tool before and after the point can be used to generate a buffer with a second distance length before and after the point, and by performing spatial geographic intersection with the geographical location of the static indicator, it can be determined whether there is a static indicator in the buffer, thereby determining whether the accident point in the current accident section meets the second condition.

[0125] Optionally, for the target accident point in the current accident segment, the distance between the target accident point and each static indicator can be determined to obtain multiple distances, and whether the current accident segment meets the second condition is determined through the relationship between the minimum distance among the multiple distances and the second distance.

[0126] Optionally, the selection of static indicators can be adjusted according to business needs.

[0127] Exemplarily, it is possible to determine whether the distance between the target accident point and any static indicator of a sharp turn, steep slope, long uphill slope, long downhill slope, lane change point, speed limit change point, waterside section, cliff section, or ramp main road mismatch point is less than or equal to the second distance.

[0128] It should be noted that the target accident points under different conditions (such as the first condition and the second condition) are also different.

[0129] For example, the target accident point in S401 above may be an accident point where 3-4 persons died within three years; the target accident point in S402 may be an accident point where persons died within three years.

[0130] S403: Determine the ratio of the number of accident points in the current accident section to the length of the current accident section as the number of accident points per unit length of the current accident section.

[0131] Optionally, the length of the current accident section may be determined by the accident point with the smallest absolute position and the accident point with the largest absolute position among the current accident points.

[0132] S404: When the number of accident points per unit length of the current accident section is greater than or equal to a preset threshold, determine that the accident points of the current accident section meet a third condition.

[0133] It should be noted that, for the first condition, the second condition, and the third condition in the embodiment of the present application, it is not necessary to perform all judgments, that is, when the current accident segment satisfies the first condition, there is no need to judge whether the current accident segment satisfies the second condition and the third condition.

[0134] Optionally, for the first condition, the second condition and the third condition, different degrees of accident-prone area judgment criteria may be set in combination with specific business needs.

[0135] Exemplarily, there may be set up a type I accident-prone area, a type II accident-prone area, and a type III accident-prone area.

[0136] Specifically, for a Class I accident-prone area, the corresponding judgment conditions may be a1, b1, c1 as follows; for a Class II accident-prone area, the corresponding judgment conditions may be a2, b2, c2 as follows; for a Class III accident-prone area, the corresponding judgment conditions may be a3, b3, c3 as follows:

[0137] a1. In the past three years, there have been one or more road traffic accidents in which five or more people died, and the occurrence of the accidents was related to road factors.

[0138] b1. In the past three years, there have been two or more road traffic accidents in which three or more persons were killed.

[0139] c1. More than 6 fatal traffic accidents occurred in the past 3 years.

[0140] a2. In the past three years, there has been a road traffic accident in which three to four people died, and the accident was related to road factors.

[0141] b2. In the past three years, 3 to 5 traffic accidents resulting in death have occurred.

[0142] c2. In the past three years, there have been more than six traffic accidents resulting in casualties.

[0143] a3. In the past three years, 1-2 fatal traffic accidents have occurred, and the accidents are related to road factors.

[0144] b3. In the past three years, 3-5 traffic accidents resulting in casualties have occurred.

[0145] c3. In the past three years, there have been a lot of road traffic accidents (including simple accidents).

[0146] Optionally, in combination with the above conditions a1-a3, b1-b3, c1-c3, when the current accident section is determined to be an accident-prone area, the level corresponding to the accident-prone area can be further determined.

[0147] Optionally, for b1 and c1, they can be understood as the first condition for a Class I accident-prone area, and for a1, it can be understood as the second condition for a Class I accident-prone area; for b2 and c2, they can be understood as the second condition for a Class II accident-prone area, and for a2, it can be understood as the second condition for a Class II accident-prone area; for b3, it can be understood as the first condition for a Class III accident-prone area, and for a3, it can be understood as the second condition for a Class III accident-prone area, and for c3, it can be understood as the third condition for a Class III accident-prone area.

[0148] It should be noted that the occurrence of road traffic accidents is prominent, which can be understood as the number of accident points per unit length of the accident section being greater than or equal to a preset threshold.

[0149] Optionally, the preset threshold in S404 may be determined in combination with specific business requirements and relevant industry standards.

[0150] Exemplarily, the preset threshold may be 40, 50, etc.

[0151] In a possible implementation, the embodiment of the present application provides a method for identifying accident-prone areas, and the specific process can be as follows: Figure 6 As shown, firstly, the accident (accident point) data acds is initialized according to the road number, and the accidents are sorted according to the absolute position, and the preset threshold acdnum_threshold is input to determine whether the road type corresponding to the data is an expressway or a first-class highway. When the road type is an expressway or a first-class highway, the accident-prone point length threshold point_threshold = 1000 meters and the accident-prone section length threshold line_threshold = 4000 meters are determined; when the road type is not an expressway or a first-class highway, the accident-prone point length threshold point_threshold = 500 meters and the accident-prone section length threshold line_threshold = 2000 meters are determined.

[0152] Furthermore, the accidents (i.e. accident points) in acds are traversed, and the current accident is defined as acd, and the absolute position of the current accident is d. All data (accidents) in acds whose absolute positions are greater than d and less than d+line_threshold are selected, and list_acd is formed with the current accident acd, and it is determined whether the data in list_acd meets the conditions of accident-prone areas (the first condition, the second condition, or the third condition).

[0153] Specifically, define type=1 (i.e., a type of accident-prone area), determine whether list_acd satisfies the first condition in the type-type accident-prone area standard, and when list_acd satisfies the first condition in the type-type accident-prone area standard, calculate the length lengh of list_acd; when list_acd does not satisfy the first condition in the type-type accident-prone area standard, further determine whether list_acd satisfies the second condition in the type-type accident-prone area standard. When list_acd satisfies the second condition in the type-type accident-prone area standard, calculate the length lengh of list_acd; when list_acd does not satisfy the second condition in the type-type accident-prone area standard, set type=type+1, and determine whether type is equal to 4.

[0154] Specifically, Figure 6 As shown, in combination with the above S401 and S402, determining whether list_acd satisfies the second condition in the type class accident-prone area standard may include first determining whether the number of accident points in list_acd whose casualty information meets the casualty conditions within a preset time period, that is, whether the number of target accident points meets the casualty conditions, and when the number of target accident points meets the casualty conditions, traversing the target accident points in list_acd to determine whether there is at least one target accident point with a static indicator within a range of 1000 meters before and after, and when there is a target accident point with a static indicator within a range of 1000 meters before and after, determining whether list_acd meets the second condition in the type class accident-prone area standard.

[0155] When type≠4, re-judge whether the data in list_acd meets the conditions of the type accident-prone area standard. When type=4, calculate the length lengh of list_acd and determine the number of accidents per kilometer of list_acd, and then judge whether the number of accidents per kilometer is less than the preset threshold acdnum_threshold. When the number of accidents per kilometer is less than the preset threshold acdnum_threshold, calculate the length lengh of list_acd. When the number of accidents per kilometer is less than the preset threshold acdnum_threshold, delete acd from acds, and judge whether acds has been traversed. If acds has been traversed, it ends, otherwise re-traverse the accidents in acds.

[0156] Furthermore, after calculating the length lengh of list_acd, determine whether lengh is less than the length threshold point_threshold of the accident-prone point. When lengh is less than the length threshold point_threshold of the accident-prone point, determine list_acd as an accident-prone point; when lengh is greater than or equal to the length threshold point_threshold of the accident-prone point, determine list_acd as an accident-prone area.

[0157] After determining that list_acd is a high-accident point or high-accident location, delete the accident point data included in list_acd from acds, and determine whether acds has been traversed. If acds has been traversed, the process ends; otherwise, traverse the accidents in acds again.

[0158] It should be noted that lengh can be the difference between the maximum absolute position in list_acd and the minimum absolute position in list_acd, that is, lengh = the maximum absolute position in list_acd - the minimum absolute position in list_acd. Judging whether type is equal to 4 can be understood as judging whether the current type is a Class III accident-prone area, that is, whether it is necessary to consider whether list_acd meets the third condition.

[0159] In the embodiment of the present application, whether the current accident section meets the conditions of an accident-prone area is evaluated by taking the target accident point as the object, and static indicators are introduced to judge the correlation between accidents and road factors. In addition, the accident sections with more frequent accidents or more prominent situations are screened according to the number of accident points per unit length of the accident section, so as to determine the accident-prone areas based on the above three dimensions, and further improve the accuracy of identifying the accident-prone areas.

[0160] In one design, Figure 7 As shown, the accident-prone area identification method provided in the embodiment of the present application further includes S501-S503:

[0161] S501. For a first accident-prone area on a target road, determine a plurality of first target static indicators on the target road whose distance from the first accident-prone area is less than or equal to a third distance.

[0162] Among them, the first accident-prone area is any accident-prone area in the target road; the types of the multiple first target static indicators are different, and each of the multiple first target static indicators is a static indicator of the same type that is closest to the first accident-prone area.

[0163] Optionally, the third distance may be determined in combination with specific business requirements and relevant industry standards.

[0164] For example, after many experiments and data statistics, it is found that when the third distance is 1000 meters, the static indicators within this range are strongly correlated with accident-prone areas, and the third distance can be determined to be 1000 meters.

[0165] Optionally, the third distance may also be 700 meters, 850 meters, etc.

[0166] Optionally, for the first accident-prone place, geographic information data, such as R-table data, can be used to generate a spatial linearity of 1000 meters (third distance) before and after the first accident-prone place according to the direction of travel, and then for each static indicator, if the static indicator exists within 1000 meters before and after the first accident-prone place, the static indicator is associated with the accident-prone place, and the static indicator of the static indicator that is closest to the first accident-prone place is determined as the first target static indicator.

[0167] S502: Determine the distance risk value of each first target static indicator to obtain the distance risk values ​​of multiple first target static indicators.

[0168] Among them, the distance risk value is used to indicate the risk impact degree of each first target static indicator on the first accident-prone area.

[0169] It should be noted that, for the various types of static indicators associated with the first accident-prone area, each type of static indicator has a first target static indicator, and then the distance risk value of each first target static indicator is determined.

[0170] Optionally, the risk impact of each first target static indicator on the first accident-prone area may be evaluated in combination with the distance between each first target static indicator and the first accident-prone area, thereby determining the distance risk value of each first target static indicator.

[0171] Optionally, the distance risk value of each first target static indicator may be determined by combining the distance between each first target static indicator and the first accident-prone location and the proportion of each first target static indicator in all static indicators associated with the first accident-prone location.

[0172] For example, for a certain accident-prone area, there are a total of 20 static indicators within 800 meters (the third distance) before and after, including 5 type a static indicators, and the type a static indicator closest to the accident-prone area is 0 meters away from the accident-prone area, then the distance risk value of the first target static indicator a is determined to be (1-0 / 800)*5 / 20=0.25.

[0173] S503. Generate a static indicator risk assessment result of the first accident-prone area based on the distance risk values ​​of the plurality of first target static indicators.

[0174] Among them, the static indicator risk assessment result is used to indicate the result of ranking the risk impact of different first target static indicators on the first accident-prone area.

[0175] Optionally, after determining the distance risk value of each first target static indicator, the distance risk values ​​may be sorted in descending order according to their sizes, thereby determining the static indicator risk assessment result of the first accident-prone area.

[0176] It should be noted that when a certain accident-prone area does not have a first target static indicator whose distance from the first accident-prone area is less than or equal to the third distance in the target road, the static indicator risk assessment result of the certain accident-prone area is determined to be none.

[0177] Optionally, for accident-prone areas where the static indicator risk assessment result is none, the generation of the accident-prone areas may be related to weather factors and human factors.

[0178] In an embodiment of the present application, after determining accident-prone areas, the distance risk value of each static indicator can be further determined in combination with the static indicators associated with the accident-prone areas, so as to realize static indicator risk analysis of accident-prone areas, realize road safety risk assessment, and improve the accuracy of road safety assessment.

[0179] In one design, Figure 8 As shown, in a method for identifying accident-prone areas provided in an embodiment of the present application, the "determining the distance risk value of each first target static indicator" in the above S502 includes S601-S602:

[0180] S601. Obtain the distance between each first target static indicator and the first accident-prone location, and obtain a distance risk calculation rule for each first target static indicator.

[0181] Therein, the distance risk calculation rules correspond one-to-one to the distance risk relationship of the static indicator, and the distance risk relationship is used to indicate the degree of danger corresponding to locations at different distances from the static indicator.

[0182] Optionally, after determining each static indicator associated with the first accident-prone area, the shortest distance from the first accident-prone area to each static indicator may be calculated.

[0183] Optionally, the shortest distance from the first accident-prone place to a certain static indicator may be understood as the shortest distance between each static indicator in the certain static indicator and the first accident-prone place.

[0184] Exemplarily, for the first accident-prone area and static indicator type A, within 1000 meters (the third distance) before and after the first accident-prone area, there are static indicator a1, static indicator a2 and static indicator a2, wherein the distance d1 between the first accident-prone area and the static indicator a1 is 900 meters, the distance d2 between the first accident-prone area and the static indicator a2 is 600 meters, and the distance d3 between the first accident-prone area and the static indicator a3 is 100 meters, then it is determined that the shortest distance from the first accident-prone area to the static indicator A is 100 meters.

[0185] It should be noted that when a static indicator is located inside the first accident-prone area, such as between two accident points in the accident-prone area, it is considered that the distance between the first accident-prone area and the static indicator is 0.

[0186] Optionally, the distance risk calculation rule of the static indicator of the first target may be a functional relationship between the distance and the danger level corresponding to the first target, that is, a corresponding relationship between the distance and the risk value.

[0187] Exemplarily, for the first target static indicator A, the distance risk calculation rule may be: distance risk value=1-distance / 1000.

[0188] Optionally, the distance risk relationship can be determined by statistically analyzing relevant information of the accident point based on specific business needs.

[0189] Exemplarily, the distance risk relationship may include: being located on a static indicator is the most dangerous, being closer to the static indicator is more dangerous, and having no obvious relationship with the distance from the static indicator.

[0190] Optionally, for the most dangerous distance risk relationship on the static indicator, it can be understood that the corresponding danger level is the highest when it is near the static indicator (such as within 50 meters of the static indicator), and the corresponding danger level is lower when it is not outside the static indicator (or when it is not near the static indicator, the corresponding danger level does not change significantly with the increase of the distance from the static indicator); for the distance risk relationship in which the closer to the static indicator, the more dangerous it is, it can be understood that the corresponding danger level gradually decreases with the increase of the distance from the static indicator; for the distance risk relationship in which there is no obvious relationship with the distance to the static indicator, it can be understood that there is no obvious relationship between the corresponding danger level and the change in the distance between the static indicator.

[0191] Optionally, the distance risk calculation rules corresponding to each distance risk relationship can be adjusted according to different business needs.

[0192] Exemplarily, taking the three types of distance risk relationships as examples, including: the most dangerous when located on the static indicator, the more dangerous when closer to the static indicator, and no obvious relationship with the distance to the static indicator, for the distance risk relationship that is the most dangerous when located on the static indicator, the corresponding distance risk calculation rule may be that when the first accident-prone area is near the static indicator (for example, the distance from the static indicator is less than 50 meters), the distance risk value of the static indicator is determined to be 0.8, and when the first accident-prone area is not near the static indicator, the distance risk value of the static indicator is determined to be 1; for the distance risk relationship that is more dangerous when closer to the static indicator, the corresponding distance risk calculation rule may be distance risk value = 1-distance between the accident-prone area and the static indicator / third distance; for the distance risk relationship that has no obvious relationship with the distance to the static indicator, the corresponding distance risk calculation rule may be that the distance risk value is always equal to 1.

[0193] S602: Determine the distance risk value of each first target static indicator according to the distance between each first target static indicator and the first accident-prone location and the distance risk calculation rule of each first target static indicator.

[0194] Optionally, based on the distance risk calculation rule of each first target static indicator, the distance risk value of the corresponding first target static indicator can be determined according to the distance between the first target static indicator and the first accident-prone location.

[0195] Exemplarily, for the first target static indicator A, the distance risk relationship is that the closer to the static indicator, the more dangerous it is. The third distance is 1000, and the distance risk calculation rule is: distance risk value = 1-the distance between the accident-prone area and the static indicator / 1000. For the first accident-prone area, when the distance between the first target static indicator A and the first accident-prone area is 400 meters, then for the first accident-prone area, the distance risk value of the first target static indicator A = 1-400 / 1000 = 1-0.4 = 0.6.

[0196] In the embodiment of the present application, the distance risk calculation rule of each first target static indicator is determined according to the distance risk relationship of each first target static indicator, and then the distance risk value of each first target static indicator is determined according to the distance between each first target static indicator and the first accident-prone area and the distance risk calculation rule of each first target static indicator. Thus, the corresponding distance risk value is determined based on the distance between the specific first target static indicator and the accident-prone area, so as to improve the accuracy and rationality of the static indicator risk assessment of the accident-prone area.

[0197] In one design, Fig. 9 As shown, in an accident-prone area identification method provided in an embodiment of the present application, the method further includes S701-S702:

[0198] S701. Obtain accident point distribution data of a first type of static indicators in a target road.

[0199] Among them, the first type of static indicator is any type of static indicator in the target road; the accident point distribution data includes the distance between each static indicator and the corresponding accident point under the first type of static indicator and the number of corresponding accident points; the distance between each static indicator and the corresponding accident point is less than or equal to the fourth distance, and each static indicator is the static indicator of the first type of static indicator that is closest to the corresponding accident point.

[0200] Optionally, the fourth distance may be determined in combination with specific business requirements and relevant industry standards.

[0201] For example, after many experiments and data statistics, it is found that when the fourth distance is 1000 meters, the static indicators within this range are strongly correlated with accident-prone areas, and it can be determined that the fourth distance is 1000 meters.

[0202] Optionally, the fourth distance may also be 800 meters, 500 meters, etc.

[0203] Optionally, for any accident point, geographic information data, such as R table data, can be used to generate a spatial linear relationship 1000 meters before and after (the fourth distance) of any accident point according to the direction of travel, and then for each static indicator, if the static indicator exists within 1000 meters before and after any accident point, each static indicator in the static indicator is associated with the accident point, and the shortest distance from any accident point to the static indicator is calculated, and the accident point is associated with the target static indicator in the static indicator that is closest to the accident point, so as to determine the static indicator associated with each accident point.

[0204] It can be understood that according to the above-mentioned step of "associating any accident point with the target static indicator among the static indicators that is closest to any accident point", for the accident points where static indicators exist within the fourth distance around them, the static indicator associated with the accident point and the shortest distance between the associated static indicators will be obtained.

[0205] Furthermore, taking each static indicator as an object, for any static indicator, the accident point associated with the static indicator and the distance between each associated accident point are determined, so as to statistically calculate the accident point distribution data corresponding to each type of static indicator.

[0206] S702: Determine the distance risk relationship of the first type of static indicators according to the accident point distribution data.

[0207] Optionally, the relationship between the distance between the static indicator corresponding to each static indicator in the first type of static indicators and the accident point and the number of accident points can be determined based on the accident point distribution data, thereby determining the relationship between the distance between the static indicator corresponding to the first type of static indicator and the accident point and the number of accident points, and then determining the distance risk relationship of the first type of static indicator based on this relationship.

[0208] For example, based on the accident point distribution data, it is found that for type A static indicators, the number of accident points is the largest when the distance is within 50 meters of the static indicator, and the number of accident points is smaller after exceeding 50 meters. Moreover, as the distance from the static indicator increases, the number of accident points does not change significantly. Therefore, it can be determined that the distance risk relationship of type A static indicators is the most dangerous when located on the static indicator.

[0209] In an embodiment of the present application, the distance risk relationship of the first type of static indicators is determined based on the accident point distribution data of the first type of static indicators in the target road, so as to achieve the difference in the accident point distribution data of each type of static indicators and determine the distance risk relationship for each type of static indicators, so as to improve the rationality of the determination of the distance risk relationship.

[0210] In one design, Fig.10 As shown, in a method for identifying accident-prone areas provided in an embodiment of the present application, the above S503 includes S801-S802:

[0211] S801. Determine the product of the weight corresponding to the type of each first target static indicator and the distance risk value of each first target static indicator to obtain multiple products.

[0212] S802. Sort multiple products to obtain a static indicator risk assessment result.

[0213] Optionally, the weight corresponding to each type of the first target static indicator may be determined based on information such as expert experience and specific business requirements.

[0214] Exemplarily, the weight corresponding to each type of static indicator may be determined in combination with information such as the number of each type of static indicators or the number of accident points associated with each type of static indicators.

[0215] Optionally, after obtaining the product of the weight corresponding to the type of each first target static indicator and the risk value of the distance from each first target static indicator, the products can be sorted according to the size of the product results (for example, sorting the product results from large to small) to obtain the static indicator risk assessment result.

[0216] In an embodiment of the present application, after obtaining the distance risk value of each first target static indicator, the distance risk value of each first target static indicator is further weighted in combination with the weight corresponding to the type of each first target static indicator, so as to further improve the accuracy of the static indicator risk assessment of accident-prone areas.

[0217] In one design, Fig.11 As shown, in an accident-prone area identification method provided in an embodiment of the present application, S901-S902 are also included:

[0218] S901. Obtain the number of accident points corresponding to each static indicator under the first type of static indicators, and the length of each static indicator.

[0219] Among them, the first type of static indicator is any type of static indicator in the target road; the distance between each static indicator and the corresponding accident point is less than or equal to the fifth distance, and each static indicator is the static indicator of the first type of static indicator that is closest to the corresponding accident point.

[0220] S902: Determine the weight of the first type of static indicator as the ratio of the sum of the numbers of accident points corresponding to all static indicators under the first type of static indicator to the sum of the lengths of all static indicators.

[0221] Optionally, the length of each static indicator can be understood as the actual length of the static indicator. For example, for a bridge static indicator, the length of the static indicator is the length of the bridge itself; for a tunnel static indicator, the length of the static indicator is the length of the tunnel itself.

[0222] Optionally, the ratio of the sum of the number of accident points corresponding to all static indicators under the first type of static indicators to the sum of the lengths of all static indicators can also be understood as the number of accidents per unit length of this type of static indicators.

[0223] Optionally, considering that static indicators may be point-type static indicators, such as lane change points, speed limit change points, toll booths, etc. Therefore, when determining the ratio of the sum of the number of accident points corresponding to all static indicators under the first type of static indicators to the sum of the lengths of all static indicators, the length of each static indicator can be set to the length of the static indicator itself plus a preset length (such as 200 meters), as shown in Formula 1:

[0224]

[0225] Among them, α is the weight corresponding to the first type of static indicator, k is the number of static indicators of the first type of static indicator, h i is the length of the i-th static index, m i is the number of accident points associated with the i-th static indicator.

[0226] In an embodiment of the present application, the weight of each type of static indicator is determined based on the number of accident points corresponding to each static indicator under each type of static indicator and the length of each static indicator to improve the rationality of determining the weight of each type of static indicator.

[0227] In one design, Fig.12 As shown, a method for identifying accident-prone areas provided in an embodiment of the present application further includes S1001-S1003:

[0228] S1001. Obtain the number of accident points corresponding to each static indicator under the first type of static indicators, and the length of each static indicator.

[0229] Among them, the first type of static indicator is any type of static indicator in the target road; the distance between each static indicator and the corresponding accident point is less than or equal to the fifth distance, and each static indicator is the static indicator of the first type of static indicator that is closest to the corresponding accident point.

[0230] S1002. Determine the ratio of the sum of the number of accident points corresponding to all static indicators under the first type of static indicators to the sum of the lengths of all static indicators as the first ratio of the first type of static indicators, and obtain the first ratio of all types of static indicators.

[0231] S1003: Determine the ratio of the first ratio of the first type of static indicators to the sum of the first ratios of all types of static indicators as the weight of the first type of static indicators.

[0232] Optionally, the fifth distance may be determined in combination with specific business requirements and relevant industry standards.

[0233] For example, after many experiments and data statistics, it is found that when the fifth distance is 1000 meters, the static indicators within this range are strongly correlated with accident-prone areas, and it can be determined that the fifth distance is 1000 meters.

[0234] Optionally, the fifth distance may also be 800 meters, 500 meters, etc.

[0235] It should be noted that different distances can be used for the second distance, third distance, fourth distance and fifth distance in the embodiment of the present application, such as the second distance is 1000 meters, the third distance is 800 meters, the fourth distance is 900 meters, and the fifth distance is 700 meters. The selection of distance can be determined in combination with specific experimental data and business needs.

[0236] Optionally, since the second distance, the third distance, the fourth distance and the fifth distance in the embodiment of the present application all serve to associate accident-prone areas (or accident points) with static indicators, when determining the second distance, the third distance, the fourth distance and the fifth distance, they can be set to the same distance, such as determining that the second distance, the third distance, the fourth distance and the fifth distance are all 1000 meters.

[0237] Optionally, after determining the first ratio of the first type of static indicator, the first ratio of the first type of static indicator may be normalized, and the normalized first ratio may be determined as the weight of the first type of static indicator.

[0238] Specifically, the weight of each type of static indicator can be determined by Formula 2:

[0239]

[0240] Among them, β o is the weight of the static indicator of type o, N o is the first ratio of the static index of type o, q is the number of types of static indexes, N l It is the first ratio of the static index of type l.

[0241] Exemplarily, the weight of each type of static indicator determined by Formula 2 may be the weight shown in Table 3.

[0242] In one implementation, Fig.13 As shown, an accident-prone area identification method provided in an embodiment of the present application can first realize the identification and generation of static risk indicators (static indicators) and the identification of accident-prone areas based on a preset data source, and then complete the risk analysis of accident-prone areas based on the static risk indicators.

[0243] Optional, such as Fig.13 As shown, the data source may include basic map data, historical road condition data, and accident data (ie, accident data corresponding to the accident point).

[0244] Optional, such as Fig.13 As shown, the identification and generation of static risk indicators (i.e., static indicators) can be achieved through basic map data and historical road condition data. The static risk indicators can include line indicators (such as sharp bends, steep slopes, long uphill slopes, long downhill slopes, and frequently congested sections) and point indicators (such as lane change points, speed limit change points, frequently occurring speed mutation points, and other static indicators).

[0245] Optional, such as Fig.13 As shown, the identification of accident-prone areas can be divided into the identification of accident-prone points / sections on expressways and the identification of accident-prone points / sections on ordinary roads according to the road type and length threshold.

[0246] Optional, such as Fig.13 As shown, for the risk analysis of accident-prone areas, we can first complete the association between accident data and static risk indicators, as well as the analysis of the correlation between accident data and static risk indicators, and then associate the accident-prone areas with static indicators to achieve static (indicator) risk analysis of accident-prone areas.

[0247] Table 3

[0248] index Weight bridge 0.049928483 tunnel 0.065845667 Frequently congested roads 0.113231934 Road sections prone to sudden acceleration 0.022672438 Road sections prone to sudden deceleration 0.143924089 Long downhill 0.000421573 Long uphill 0.000445515 Lane change point 0.084042591 Speed ​​limit change point 0.055027771 The ramp does not match the main road 0.109447029 Cliff section 0.043092043 Linshui Road 0.040658851 Long straight line 0.029369967 Sharp bend 0.013731340 steep slope 0.018988108 Weaving section length is too short 0.209172601

[0249] The above mainly introduces the solution provided by the embodiment of the present application from the perspective of the method. In order to realize the above functions, it includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiment disclosed herein, the embodiment of the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0250] The embodiment of the present application can divide the functional modules of an accident-prone area identification device according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of software functional modules. Optionally, the division of modules in the embodiment of the present application is schematic and is only a logical functional division. There may be other division methods in actual implementation.

[0251] Fig.14 This is a schematic diagram of the structure of a device for identifying accident-prone areas provided in an embodiment of the present application. Fig.14 As shown, the accident-prone area identification device 40 is used to improve the rationality and accuracy of accident-prone area identification, for example, to perform Figure 2 A method for identifying accident-prone areas is shown. The accident-prone area identification device 40 includes: an acquisition unit 401, a processing unit 402, and a determination unit 403.

[0252] The acquisition unit 401 is used to acquire the absolute position information of multiple accident points included in the target road.

[0253] The processing unit 402 is used to sort the multiple accident points according to the absolute position information of the multiple accident points to obtain an accident point sequence.

[0254] The determination unit 403 is used to determine the current accident road section corresponding to the current accident point in the accident point sequence; the current accident road section includes the current accident point and the accident points in the accident point sequence that are located after the current accident point and whose distance to the current accident point is less than or equal to the first distance.

[0255] Processing unit 402 is used to update the next accident point in the accident point sequence of the current accident section to the current accident point when the current accident section is an accident-prone area, until the updated current accident point is the last accident point in the accident point sequence; when the current accident section is not an accident-prone area, update the next accident point in the accident point sequence of the current accident point to the current accident point, until the updated accident point is the last accident point in the accident point sequence.

[0256] In one design, the determination unit 403 is used to determine that the current accident section is an accident-prone area when the accident point of the current accident section meets any one of the first condition, the second condition and the third condition.

[0257] Among them, the first condition is used to indicate the number of accident points whose casualties meet the casualty conditions within a preset time period; the second condition is used to indicate the number of accident points whose casualties meet the casualty conditions within a preset time period, and the accidents at the accident points are related to road factors; the third condition is used to indicate the number of accident points in the current accident section.

[0258] The determination unit 403 is used to determine that the current accident section is not an accident-prone area when the current accident section does not meet the first condition, the second condition and the third condition.

[0259] In one design, the determination unit 403 is configured to determine that the accident points in the current accident section meet the first condition if the number of target accident points in the current accident section meets the casualty condition.

[0260] Among them, the target accident point is the accident point where the casualty information meets the casualty conditions within a preset time period.

[0261] The determination unit 403 is used to determine that the accident points in the current accident section meet the second condition if the number of target accident points in the current accident section meets the casualty condition and if the distance between the target accident point and any static indicator is less than or equal to the second distance.

[0262] The determination unit 403 is used to determine the ratio of the number of accident points in the current accident section to the length of the current accident section as the number of accident points per unit length of the current accident section.

[0263] The determination unit 403 is used to determine that the accident points of the current accident section meet the third condition when the number of accident points per unit length of the current accident section is greater than or equal to a preset threshold.

[0264] In one design, the determination unit 403 is used to determine, for a first accident-prone location in a target road, a plurality of first target static indicators whose distance from the first accident-prone location in the target road is less than or equal to a third distance.

[0265] Among them, the first accident-prone area is any accident-prone area in the target road; the types of the multiple first target static indicators are different, and each of the multiple first target static indicators is a static indicator of the same type that is closest to the first accident-prone area.

[0266] The determination unit 403 is used to determine the distance risk value of each first target static indicator to obtain the distance risk values ​​of multiple first target static indicators.

[0267] Among them, the distance risk value is used to indicate the risk impact degree of each first target static indicator on the first accident-prone area.

[0268] The processing unit 402 is used to generate a static indicator risk assessment result of the first accident-prone area according to the distance risk values ​​of multiple first target static indicators.

[0269] Among them, the static indicator risk assessment result is used to indicate the result of ranking the risk impact of different first target static indicators on the first accident-prone area.

[0270] In one design, the acquisition unit 401 is used to obtain the distance between each first target static indicator and the first accident-prone location, and to obtain the distance risk calculation rule for each first target static indicator.

[0271] Therein, the distance risk calculation rules correspond one-to-one to the distance risk relationship of the static indicator, and the distance risk relationship is used to indicate the degree of danger corresponding to locations at different distances from the static indicator.

[0272] The determination unit 403 is used to determine the distance risk value of each first target static indicator according to the distance between each first target static indicator and the first accident-prone area and the distance risk calculation rule of each first target static indicator.

[0273] In one design, the acquisition unit 401 is used to obtain accident point distribution data of a first type of static indicators in a target road.

[0274] Among them, the first type of static indicator is any type of static indicator in the target road; the accident point distribution data includes the distance between each static indicator and the corresponding accident point under the first type of static indicator and the number of corresponding accident points; the distance between each static indicator and the corresponding accident point is less than or equal to the fourth distance, and each static indicator is the static indicator of the first type of static indicator that is closest to the corresponding accident point.

[0275] The determination unit 403 is used to determine the distance risk relationship of the first type of static indicators according to the accident point distribution data.

[0276] In one design, the determination unit 403 is used to determine the product of the weight corresponding to the type of each first target static indicator and the risk value of the distance of each first target static indicator to obtain multiple products.

[0277] The processing unit 402 is used to sort the multiple products to obtain a static indicator risk assessment result.

[0278] In one design, the acquisition unit 401 is used to obtain the number of accident points corresponding to each static indicator under the first type of static indicators, and the length of each static indicator.

[0279] Among them, the first type of static indicator is any type of static indicator in the target road; the distance between each static indicator and the corresponding accident point is less than or equal to the fifth distance, and each static indicator is the static indicator of the first type of static indicator that is closest to the corresponding accident point.

[0280] The determination unit 403 is used to determine the ratio of the sum of the number of accident points corresponding to all static indicators under the first type of static indicators to the sum of the lengths of all static indicators as the weight of the first type of static indicators.

[0281] In one design, the acquisition unit 401 is used to obtain the number of accident points corresponding to each static indicator under the first type of static indicators, and the length of each static indicator.

[0282] Among them, the first type of static indicator is any type of static indicator in the target road; the distance between each static indicator and the corresponding accident point is less than or equal to the fifth distance, and each static indicator is the static indicator of the first type of static indicator that is closest to the corresponding accident point.

[0283] The determination unit 403 is used to determine the ratio of the sum of the number of accident points corresponding to all static indicators under the first type of static indicators to the sum of the lengths of all static indicators as the first ratio of the first type of static indicators, and obtain the first ratio of all types of static indicators.

[0284] The determining unit 403 is configured to determine the ratio of the first ratio of the first type of static indicators to the sum of the first ratios of all types of static indicators as the weight of the first type of static indicators.

[0285] In the case of implementing the functions of the above-mentioned integrated modules in the form of hardware, the embodiment of the present application provides a possible structural diagram of the electronic device involved in the above-mentioned embodiment. Fig.15 As shown, an electronic device 70 is used to improve the rationality and accuracy of accident-prone areas identification, for example, for performing Figure 2 The electronic device 70 includes a processor 701, a memory 702 and a bus 703. The processor 701 and the memory 702 may be connected via the bus 703.

[0286] The processor 701 is the control center of the communication device, which can be a processor or a general term for multiple processing elements. For example, the processor 701 can be a general-purpose central processing unit (CPU) or other general-purpose processors. Among them, the general-purpose processor can be a microprocessor or any conventional processor.

[0287] As an embodiment, the processor 701 may include one or more CPUs, such as Fig.15 CPU 0 and CPU 1 are shown in .

[0288] The memory 702 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these.

[0289] As a possible implementation, the memory 702 may exist independently of the processor 701, and the memory 702 may be connected to the processor 701 via a bus 703, and is used to store instructions or program codes. When the processor 701 calls and executes the instructions or program codes stored in the memory 702, a method for identifying accident-prone areas provided in an embodiment of the present application can be implemented.

[0290] In another possible implementation, the memory 702 may also be integrated with the processor 701 .

[0291] The bus 703 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.15 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0292] It should be pointed out that Fig.15 The structure shown does not constitute a limitation on the electronic device 70. Fig.15 In addition to the components shown, the electronic device 70 may include more or fewer components than shown, or combine certain components, or arrange the components differently.

[0293] As an example, combining Fig.14 The functions implemented by the acquisition unit 401, the processing unit 402 and the determination unit 403 in the accident-prone area identification device 40 are similar to those Fig.15 The function of processor 701 in is the same.

[0294] Optional, such as Fig.15 As shown, the electronic device 70 provided in the embodiment of the present application may further include a communication interface 704 .

[0295] The communication interface 704 is used to connect with other devices through a communication network. The communication network may be Ethernet, wireless access network, wireless local area network (WLAN), etc. The communication interface 704 may include a receiving unit for receiving data and a sending unit for sending data.

[0296] In one design, in the electronic device provided in the embodiment of the present application, the communication interface can also be integrated into the processor.

[0297] Through the description of the above implementation methods, those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above functional units is used as an example. In practical applications, the above functions can be assigned to different functional units as needed, that is, the internal structure of the device can be divided into different functional units to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0298] An embodiment of the present application also provides a computer-readable storage medium, in which instructions are stored. When a computer executes the instructions, the computer executes each step in the method flow shown in the above method embodiment.

[0299] An embodiment of the present application provides a computer program product including instructions. When the instructions are executed on a computer, the computer is caused to execute a method for identifying accident-prone areas in the above method embodiment.

[0300] Among them, the computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, and a hard disk. Random Access Memory (RAM), Read-Only Memory (ROM), Erasable Programmable Read Only Memory (EPROM), registers, hard disks, optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above, or any other form of computer-readable storage medium of numerical value in the art. An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in a specific application integrated circuit (Application Specific Integrated Circuit, ASIC). In the embodiments of the present application, a computer-readable storage medium may be any tangible medium that contains or stores a program, which may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0301] Since the electronic device, computer-readable storage medium, and computer program product in the embodiments of the present application can be applied to the above-mentioned method, the technical effects that can be obtained can also refer to the above-mentioned method embodiments, and the embodiments of the present application will not be repeated here.

[0302] The embodiment of the present application also provides a computer program product, including a computer program, which, when executed by a processor, can implement the accident-prone area identification method in the above embodiment.

[0303] The above are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application should be included in the protection scope of the present application.

Claims

1. A method for identifying accident-prone areas, characterized in that: The method comprises: Obtaining absolute location information of multiple accident points included in the target road; sorting the multiple accident points according to the absolute position information of the multiple accident points to obtain an accident point sequence; Determine a current accident segment corresponding to a current accident point in the accident point sequence; the current accident segment includes the current accident point and an accident point in the accident point sequence that is located after the current accident point and whose distance from the current accident point is less than or equal to a first distance; If the current accident section is an accident-prone area, the next accident point of the current accident section in the accident point sequence is updated to the current accident point, until the updated current accident point is the last accident point in the accident point sequence; if the current accident section is not an accident-prone area, the next accident point of the current accident point in the accident point sequence is updated to the current accident point, until the updated accident point is the last accident point in the accident point sequence; In the case where the number of target accident points in the current accident section meets the casualty condition, determining that the accident points in the current accident section meet the first condition; the target accident point is an accident point whose casualty information meets the casualty condition within a preset time period; When the number of target accident points in the current accident section meets the casualty condition, if the distance between the target accident point and any static index is less than or equal to the second distance, it is determined that the accident point of the current accident section meets the second condition; The ratio of the number of accident points in the current accident section to the length of the current accident section is determined as the number of accident points per unit length of the current accident section; When the number of accident points per unit length of the current accident section is greater than or equal to a preset threshold, determining that the accident points of the current accident section meet a third condition; When the accident point of the current accident section satisfies any one of the first condition, the second condition and the third condition, determining the current accident section as an accident-prone area; For a first accident-prone area in the target road, a plurality of first target static indicators in the target road whose distance from the first accident-prone area is less than or equal to a third distance are determined; the first accident-prone area is any accident-prone area in the target road; the plurality of first target static indicators are of different types, and each of the plurality of first target static indicators is a static indicator of the same type that is closest to the first accident-prone area; Determine the distance risk value of each first target static indicator to obtain the distance risk values ​​of the multiple first target static indicators; the distance risk value is used to indicate the risk impact degree of each first target static indicator on the first accident-prone area; Based on the distance risk values ​​of the multiple first target static indicators, a static indicator risk assessment result of the first accident-prone area is generated; the static indicator risk assessment result is used to indicate the result of ranking the risk impact of different first target static indicators on the first accident-prone area.

2. The method according to claim 1, characterized in that The method further comprises: When the current accident section does not satisfy the first condition, the second condition, and the third condition, it is determined that the current accident section is not an accident-prone area.

3. The method according to claim 1, characterized in that The determining of the distance risk value of each first target static indicator includes: Obtaining accident point distribution data of a first type of static indicator in the target road; the first type of static indicator is any type of static indicator in the target road; the accident point distribution data includes the distance between each static indicator under the first type of static indicator and the corresponding accident point and the number of the corresponding accident points; the distance between each static indicator and the corresponding accident point is less than or equal to a fourth distance, and each static indicator is the static indicator of the first type of static indicator that is closest to the corresponding accident point; Determining, according to the accident point distribution data, a distance risk relationship of the first type of static indicator, wherein the distance risk relationship is used to indicate a degree of danger corresponding to locations at different distances from the static indicator; Obtaining the distance between each first target static indicator and the first accident-prone area, and obtaining a distance risk calculation rule for each first target static indicator; the distance risk calculation rule corresponds to the distance risk relationship of the static indicator one by one; The distance risk value of each first target static indicator is determined according to the distance between each first target static indicator and the first accident-prone area and the distance risk calculation rule of each first target static indicator.

4. The method according to claim 1, characterized in that: Generating the static indicator risk assessment result of the first accident-prone area according to the distance risk values ​​of the plurality of first target static indicators includes: Obtaining the number of accident points corresponding to each static indicator under the first type of static indicators and the length of each static indicator; the first type of static indicator is any type of static indicator in the target road; the distance between each static indicator and the corresponding accident point is less than or equal to the fifth distance, and each static indicator is the static indicator of the first type of static indicators that is closest to the corresponding accident point; Determine the ratio of the sum of the number of accident points corresponding to all static indicators under the first type of static indicators to the sum of the lengths of all static indicators as the first ratio of the first type of static indicators, and obtain the first ratio of all types of static indicators; Determine the ratio of the first ratio of the first type of static indicators to the sum of the first ratios of all types of static indicators as the weight of the first type of static indicators; Determine the product of the weight corresponding to the type of each first target static indicator and the distance risk value of each first target static indicator to obtain multiple products; The multiple products are sorted to obtain the static indicator risk assessment result.

5. A device for identifying accident-prone areas, characterized in that: The device comprises: an acquisition unit, a processing unit, and a determination unit; The acquisition unit is used to acquire the absolute position information of multiple accident points included in the target road; The processing unit is used to sort the multiple accident points according to the absolute position information of the multiple accident points to obtain an accident point sequence; The determining unit is used to determine a current accident section corresponding to a current accident point in the accident point sequence; the current accident section includes the current accident point and an accident point in the accident point sequence that is located after the current accident point and whose distance from the current accident point is less than or equal to a first distance; The processing unit is used to update the next accident point of the current accident section in the accident point sequence to the current accident point when the current accident section is an accident-prone area, until the updated current accident point is the last accident point in the accident point sequence; and to update the next accident point of the current accident point in the accident point sequence to the current accident point when the current accident section is not an accident-prone area, until the updated accident point is the last accident point in the accident point sequence; The determining unit is used to determine that the accident points of the current accident section meet the first condition if the number of target accident points in the current accident section meets the casualty condition; the target accident point is an accident point whose casualty information meets the casualty condition within a preset time period; The determining unit is configured to determine that the accident points in the current accident section meet the second condition if the distance between the target accident point and any static indicator is less than or equal to a second distance when the number of target accident points in the current accident section meets the casualty condition; The determining unit is used to determine the ratio of the number of accident points in the current accident section to the length of the current accident section as the number of accident points per unit length of the current accident section; The determining unit is configured to determine that the accident points of the current accident section meet a third condition when the number of accident points per unit length of the current accident section is greater than or equal to a preset threshold; The determining unit is configured to determine that the current accident section is an accident-prone area if the accident point of the current accident section satisfies any one of the first condition, the second condition and the third condition; The determination unit is used to determine, for a first accident-prone area in the target road, a plurality of first target static indicators in the target road whose distance from the first accident-prone area is less than or equal to a third distance; the first accident-prone area is any one of the accident-prone areas in the target road; the plurality of first target static indicators are of different types, and each of the plurality of first target static indicators is a static indicator of the same type that is closest to the first accident-prone area; The determining unit is used to determine the distance risk value of each first target static indicator to obtain the distance risk values ​​of the multiple first target static indicators; the distance risk value is used to indicate the risk impact degree of each first target static indicator on the first accident-prone area; The processing unit is used to generate a static indicator risk assessment result of the first accident-prone area based on the distance risk values ​​of the multiple first target static indicators; the static indicator risk assessment result is used to indicate the result of sorting the risk impact of different first target static indicators on the first accident-prone area.

6. An electronic device, characterized in that: include: A processor and a memory; wherein the memory is used to store one or more programs, and the one or more programs include computer-executable instructions. When the electronic device is running, the processor executes the computer-executable instructions stored in the memory to enable the electronic device to execute the accident-prone area identification method described in any one of claims 1 to 4.

7. A computer-readable storage medium storing one or more programs, characterized in that: The one or more programs include instructions, which, when executed by a computer, cause the computer to execute the accident-prone area identification method according to any one of claims 1 to 4.

8. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the accident-prone area identification method described in any one of claims 1 to 4 is implemented.

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