Road safety risk assessment method, device and equipment and storage medium

Abstract

The invention provides a road safety risk assessment method, device and equipment and a storage medium, and the method comprises the steps: obtaining basic road section information of a target road section, and the basic road section information at least comprises position information; obtaining weather prediction information of the target road section in a plurality of preset time periods based on the position information, wherein the weather prediction information comprises a weather prediction phenomenon and road visibility; obtaining a road friction coefficient of the target road section based on a weather prediction phenomenon; and inputting the basic road section information, the road friction coefficient in each preset time period and the road visibility into a road section safety risk assessment model to obtain a safety risk index of the target road section in each preset time period. Therefore, road safety can be evaluated in advance, the accuracy of road safety evaluation can be improved, and favorable support is provided for road safety early warning.

Description

Technical Field

[0001] The present application relates to the field of intelligent transportation technology, and in particular to a road safety risk assessment method, device, electronic device, computer-readable storage medium, and computer program product. Background Art

[0002] In recent years, with the continuous improvement of the road management system, road safety issues have become increasingly important. In particular, weather conditions are one of the key factors affecting road safety, and their prediction and response mechanisms need to be optimized. Traditionally, weather forecasts focus on large-scale forecasts at the macro level. This method is not accurate enough when directly applied to road safety risk assessment, and it is difficult to fully meet the needs of forward-looking and predictive judgments on road safety risks. Therefore, how to improve the accuracy of road safety risk assessment has become a research hotspot. Summary of the invention

[0003] In view of this, the present application provides a road safety risk assessment method, device, electronic device, computer-readable storage medium and computer program product, which can evaluate the safety risk index of a specified road section in advance through mesoscale weather forecast data, thereby not only being able to conduct an early assessment of road safety, but also improving the accuracy of road safety assessment, providing favorable support for road safety warnings.

[0004] In a first aspect, an embodiment of the present application provides a road safety risk assessment method, comprising: obtaining basic section information of a target section, the basic section information including at least location information; obtaining weather forecast information of the target section within multiple preset time periods based on the location information, the weather forecast information including weather forecast phenomena and road visibility; obtaining a road friction coefficient of the target section based on the weather forecast phenomena; inputting the basic section information, the road friction coefficient within each preset time period, and the road visibility into a section safety risk assessment model to obtain a safety risk index of the target section within each preset time period.

[0005] In a second aspect, an embodiment of the present application provides a road safety risk assessment device, comprising: a basic road section information acquisition module, used to acquire basic road section information of a target road section, wherein the basic road section information includes at least location information; a weather forecast information acquisition module, used to acquire weather forecast information of the target road section within multiple preset time periods based on the location information, wherein the weather forecast information includes weather forecast phenomena and road visibility; a road friction coefficient acquisition module, used to acquire the road friction coefficient of the target road section based on the weather forecast phenomena; a safety risk index acquisition module, used to input the basic road section information, the road friction coefficient within each preset time period, and the road visibility into a road section safety risk assessment model, to obtain the safety risk index of the target road section within each preset time period.

[0006] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor and a memory storing computer program instructions, wherein the computer program instructions, when executed by the processor, implement the steps of the road safety risk assessment method described in any embodiment of the present application.

[0007] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer executable program is stored, wherein when the computer executable program is executed by a processor, the steps of the road safety risk assessment method described in any embodiment of the present application are implemented.

[0008] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes computer executable instructions, wherein when the computer executable program is executed by a processor, the steps of the road safety risk assessment method described in any embodiment of the present application are implemented.

[0009] The present application provides a road safety risk assessment method, device, electronic device, computer-readable storage medium, and computer program product, which have at least the following effects:

[0010] By obtaining the basic section information of the target section, the basic situation of the designated section can be understood, and the weather forecast information of the target section in multiple preset time periods can be obtained based on the location information in the basic section information, so as to obtain the mesoscale weather forecast data in multiple forecast time periods, and the road friction coefficient of the target section can be obtained based on the weather forecast phenomenon, so that the key factors of road safety risk assessment can be obtained through the mesoscale weather forecast data. The basic section information, the road friction coefficient in each preset time period, and the road visibility are input into the section safety risk assessment model to obtain the safety risk index of the target section in each preset time period, so that the safety risk index of the target section in each preset time period can be accurately assessed in advance through the section safety risk assessment model. In this way, not only can the road safety be assessed in advance, but also the accuracy of the road safety assessment can be improved, providing favorable support for road safety warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0012] Figure 1A schematic diagram showing a flow chart of a road safety risk assessment method provided in an embodiment of the present application;

[0013] Figure 2 A schematic diagram showing the structure of a road safety risk assessment device provided by an embodiment of the present application is shown;

[0014] Figure 3 A schematic diagram showing the structure of an electronic device provided in an embodiment of the present application is shown;

[0015] Figure 4 A schematic diagram showing the structure of a computer-readable storage medium provided in an embodiment of the present application is shown;

[0016] Figure 5 A schematic diagram showing the structure of a computer program product provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0017] In order to make the above and other features and advantages of the present application more clear, the present application is further described below in conjunction with the accompanying drawings. It should be understood that the specific embodiments given herein are for the purpose of explaining to those skilled in the art and are only exemplary and not restrictive.

[0018] In the following description, many specific details are set forth to provide a thorough understanding of the present application. However, it is apparent to those skilled in the art that specific details need not be adopted to practice the present application. In other cases, well-known steps or operations are not described in detail to avoid blurring the present application.

[0019] On the one hand, an embodiment of the present application provides a road safety risk assessment method, which can be applied to a road safety risk assessment device. Figure 1 A schematic diagram showing a road safety risk assessment method provided by an embodiment of the present application is shown as follows: Figure 1 As shown, the road safety risk assessment method may include the following steps.

[0020] S11, obtaining basic section information of the target section, wherein the basic section information at least includes location information.

[0021] The target road section involved in the embodiment of the present application can be selected according to demand. For example, the target road section can be the road section ahead where the target vehicle is currently traveling, it can be the road section within the specified distance range ahead, or it can be all the road sections before reaching the destination. The basic road section information can be information on the basic attributes and status of the target road section. That is, the basic road section information can include location information, and can also include at least one of the flat curve radius, maximum longitudinal slope, vertical curve radius, road surface damage, road safety facilities and signs and signs. Among them, the road safety facilities and signs and signs can be used to evaluate the integrity, clarity and standardization of safety equipment, traffic signs and markings set on the road.

[0022] In an embodiment of the present application, the road safety risk assessment device can obtain basic road section information of the target road section from a road management related platform or navigation application software.

[0023] S12: Acquire weather forecast information of the target road section within a plurality of preset time periods based on the location information, wherein the weather forecast information includes weather forecast phenomena and road visibility.

[0024] The weather forecast information involved in this application is mesoscale weather forecast information, that is, weather forecast information within multiple preset time periods of the target road section. Weather forecast information may include, but is not limited to: weather forecast phenomena, temperature, humidity, air pressure, wind direction and speed, cloud conditions and other meteorological forecast data and road visibility calculated based on numerical weather forecast models. Among them, weather forecast phenomena may include, but are not limited to, at least one of the following: sunny, overcast, cloudy, rain, snow, fog, haze, frost, thunderstorms and hail, etc. Road visibility can be the clarity of vision.

[0025] The preset time period involved in the embodiment of the present application can be set according to the requirements. For example, the preset time period can be 1 hour, and the multiple preset time periods can be 24 hours.

[0026] In an embodiment of the present application, the road safety risk assessment device can obtain preset weather information of the target road section within multiple preset time periods from a meteorological management platform.

[0027] S13, obtaining a road friction coefficient of the target road section based on the weather forecast phenomenon.

[0028] The road friction coefficient involved in the embodiment of the present application can be a physical quantity that reflects the friction between the road surface and the tire, and is one of the indicators for measuring the driving stability of the vehicle. In the embodiment of the present application, the road safety risk assessment device can estimate the road friction coefficient of the target road section under different weather conditions based on weather forecast phenomena, using empirical formulas or database query methods.

[0029] S14, inputting basic road section information, the road friction coefficient in each preset time period, and the road visibility into a road section safety risk assessment model to obtain a safety risk index of the target road section in each preset time period.

[0030] The road section safety risk assessment model involved in the embodiment of the present application can quantitatively assess the safety risks of the target road section in different time periods based on various factors, and output a safety risk index. The safety risk index can be a quantitative indicator of the safety risk level. For example, a safety risk index below 100 corresponds to a minor accident; a safety risk index of 100 to 400 (excluding 400) corresponds to a general accident; a safety risk index of 400 to 500 (excluding 500) corresponds to a major accident; and a safety risk index of 500 or more corresponds to an extremely major accident.

[0031] In an embodiment of the present application, the road safety risk assessment device inputs basic road section information, road friction coefficient within each preset time period, and road visibility as input variables into a road section safety risk assessment model, thereby obtaining a safety risk index within each preset time period.

[0032] It should be noted that the road section safety risk assessment model can be constructed based on a prediction model, such as a linear regression model, a logistic regression model, a support vector machine, a neural network model, etc.

[0033] In the above embodiment, the basic section information of the target section is obtained to understand the basic situation of the designated section, and the weather forecast information of the target section in multiple preset time periods is obtained based on the location information in the basic section information, so as to obtain the mesoscale weather forecast data in multiple prediction time periods. And the road friction coefficient of the target section is obtained based on the weather forecast phenomenon, so that the key factors of road safety risk assessment can be obtained through the mesoscale weather forecast data. The basic section information, the road friction coefficient in each preset time period and the road visibility are input into the section safety risk assessment model to obtain the safety risk index of the target section in each preset time period, so that the safety risk index of the target section in each preset time period can be accurately assessed in advance through the section safety risk assessment model. In this way, not only can the road safety be assessed in advance, but also the accuracy of the road safety assessment can be improved, providing favorable support for road safety warning.

[0034] In some embodiments, S14, basic road section information, road friction coefficient in each preset time period, and road visibility are input into a road section safety risk assessment model to obtain a safety risk index of the target road section in each preset time period, including:

[0035] The horizontal curve radius, maximum longitudinal slope, vertical curve radius, road surface damage, completeness of road safety facilities and signs, road friction coefficient in each preset time period, and road visibility of the target road section are input into the road section safety risk assessment model to obtain the safety risk index of the target road section in each preset time period.

[0036] In the embodiment of the present application, the basic road section information may include the horizontal curve radius, the maximum longitudinal slope, the vertical curve radius, the road surface damage, and the road safety facilities and signs and signs. The road safety risk assessment device inputs the horizontal curve radius, the maximum longitudinal slope, the vertical curve radius, the road surface damage, the road safety facilities and signs and signs of the target road section, the road friction coefficient in each preset time period, and the road visibility as input variables into the road section safety risk assessment model, thereby obtaining the safety risk index in each preset time period.

[0037] In some embodiments, the road section safety risk assessment model may be a linear regression prediction model.

[0038] In one example, the road section safety risk assessment model can be expressed as the following formula.

[0039] y=β0+β1x1+β2x2+β3x3+β4x4+β5x5+β6x6+β7x7 (1)

[0040] Among them, y represents the safety risk index, β1, β2, β3, β4, β5, β6 and β7 are weight coefficients, x1 represents the road friction coefficient within the preset time period, x2 represents the road visibility within the preset time period, x3 represents the horizontal curve radius, x4 represents the maximum longitudinal slope, x5 represents the vertical curve radius, x6 represents the road surface damage degree, and x7 represents the completeness of road safety facilities and signs.

[0041] In the above embodiment, the road section safety risk assessment model is constructed using a linear regression prediction model, which enables users to more quickly master the use of the assessment model, improves assessment efficiency, and facilitates flexible adjustment of variables. It also helps users understand the impact of different factors on road section safety.

[0042] Since the inventors took into account that some road sections have not had accidents, while some road sections have had accidents, the inventors constructed corresponding safety risk assessment models according to the differences between different road sections, thereby improving the accuracy of the safety risk assessment model.

[0043] In some embodiments, in S14, the basic road section information, the road friction coefficient in each preset time period, and the road visibility are input into the road section safety risk assessment model to obtain the safety risk index of the target road section in each preset time period. The road safety risk assessment method may also include: determining whether there is historical accident information for the target road section; if so, obtaining a road section safety risk assessment model trained based on the historical accident information; if not, determining the preset risk assessment model as the road section safety risk assessment model.

[0044] The historical accident information involved in the embodiment of the present application may be detailed information on traffic accidents that occurred on the target road section in the past period of time before the current period. The historical accident information may include the historical accident level, the weather and meteorological conditions of the historical accidents, and the road visibility of the historical accidents. Among them, the historical accident level may be divided according to specified rules, for example, it may include minor accidents, general accidents, major accidents, and extremely major accidents.

[0045] The preset risk assessment model involved in the embodiment of the present application refers to a model in which the weight coefficient is a specified coefficient, wherein the specified coefficient can be set according to user experience.

[0046] In an embodiment of the present application, historical accident information can be obtained from a road management platform. The road safety risk assessment device sends a query request to the road management platform to inquire whether there is historical accident information about the target road section, so that a preliminary judgment can be made on the safety status of the target and whether there is data to support the construction of a new safety risk assessment model. If historical accident information of the target road section exists, then there is sufficient accident sample data to train a road section safety risk assessment model, thereby obtaining a trained road section safety risk assessment model. If historical accident information of the target road section does not exist, then there is no accident sample data for training, and the preset risk assessment model will be used as the road safety risk assessment model for multiple preset time periods.

[0047] The road safety risk assessment model obtained by the embodiment of the present application based on historical accident information can be obtained by the road safety risk assessment device based on historical accident information to train the road safety risk assessment model. It can also be obtained from an external computer platform for the road safety risk assessment device. In other words, the training process of the road safety risk assessment model can be carried out on the road safety risk assessment device or other computer platforms.

[0048] In addition, after the historical accident information is updated, the road section safety risk assessment model needs to be retrained and optimized.

[0049] In the above embodiment, by judging whether there is historical accident information of the target road section, it is determined whether to construct a new road section safety risk assessment model based on the historical accident information to conduct safety risk assessment on the target road, or to directly use the preset risk assessment model to conduct safety risk assessment on the target road. In this way, not only can the corresponding model be applied according to the differences of the road section, but also the existing historical data can be fully utilized to optimize the accuracy and applicability of the model.

[0050] In some embodiments, the training process of the road section safety risk assessment model may be: obtaining a plurality of accident sample data; fitting the plurality of accident sample data based on a linear regression model to obtain each weight coefficient in the road section safety risk assessment model.

[0051] The multiple accident sample data involved in the embodiment of the present application can be converted from historical accident information. Among them, according to the mapping relationship between the preset weather forecast phenomenon and the road friction coefficient, the weather and meteorology of the historical accident are converted into the road friction coefficient. And the historical accident level is converted into the corresponding safety risk index.

[0052] In an example, historical accident information can extract n accident sample data, and the accident sample data can be expressed as:

[0053]

[0054]

[0055] Among them, yn represents the safety risk index in the nth accident sample data, x1n represents the road friction coefficient in the nth accident sample data, x2n represents the road visibility in the nth accident sample data, x3n represents the horizontal curve radius in the nth accident sample data, x4n represents the maximum longitudinal slope in the nth accident sample data, x5n represents the vertical curve radius in the nth accident sample data, x6n represents the road surface damage degree in the nth accident sample data, and x7n represents the completeness of road safety facilities and signs in the nth accident sample data.

[0056] Based on the linear regression model Y=βX, fitting is performed to obtain the weight coefficient matrix β.

[0057]

[0058] In some embodiments, in S14, after the basic road section information, the road friction coefficient in each preset time period and the road visibility are input into the road section safety risk assessment model to obtain the safety risk index of the target road section in each preset time period, the road safety risk assessment method may also include: determining whether there is a target safety risk index higher than a preset threshold among the safety risk indexes in each preset time period; if so, sending the preset time period, weather forecast information and location information corresponding to the target safety risk index to a third party for safety warning.

[0059] The preset threshold involved in this application can be a critical value for measuring the safety of a road section. The preset threshold can be set according to historical data, expert experience and road safety standards. Optionally, the preset threshold can be 200. The third party can be a traffic management platform, an emergency rescue platform, a road maintenance platform and a navigation software platform. Safety warning can refer to the early discovery of potential accident hazards so that measures can be taken to deal with them.

[0060] In the embodiment of the present application, the road safety risk assessment device judges the safety risk index within each preset time period one by one, and checks whether each safety risk indication exceeds the preset threshold. If the safety risk index is found to be exceeded, the specific information corresponding to the target safety risk index is searched, such as the preset time range, the road section location and the weather forecast information, and recorded. And the road safety risk assessment device integrates the specific information corresponding to all target safety risk indexes, and sends it to a third party via SMS, the Internet or broadcasting, so that the third party can respond quickly to the above information and take corresponding measures to reduce the probability of safety accidents.

[0061] In addition, when there is no target safety risk index, the road safety risk assessment device completes the assessment of the target road section.

[0062] In the above embodiment, by evaluating the safety risk of the target road in advance, an early warning can be issued in advance during the period when accidents are prone to occur, reminding drivers, road managers and relevant departments to pay attention, thereby effectively reducing the occurrence of traffic accidents and improving the level of road management. At the same time, the preset time period, weather forecast information and location information corresponding to the target safety risk index are sent to a third party, which helps road managers and emergency response teams to accurately locate high-risk areas, formulate targeted prevention and control measures, and improve emergency response efficiency. And according to the risk assessment results, resources such as road maintenance, traffic diversion and emergency rescue can be reasonably allocated to ensure rapid response and effective response at critical moments, so as to achieve the purpose of optimizing resource allocation.

[0063] In some embodiments, the third party may be a navigation platform. After receiving the preset time period, weather forecast information and location information corresponding to the target safety risk index, the navigation platform automatically pushes the safety risk index of the target section, weather forecast information, etc. to the target vehicle when it detects that the user vehicle is about to enter the target section during the preset time period, so as to prompt the user vehicle to respond to potential dangers in a timely manner.

[0064] In some embodiments, S13, obtaining the road friction coefficient of the target road section based on the weather forecast phenomenon may include: obtaining the road friction coefficient of the target road section corresponding to the weather forecast phenomenon based on a preset mapping relationship between the weather forecast phenomenon and the road friction coefficient.

[0065] The mapping relationship between the weather forecast phenomenon and the road friction coefficient involved in the embodiment of the present application can be obtained based on the statistical analysis of a large amount of measured data of the road friction coefficient under different weather conditions. The mapping relationship can be a mapping relationship table or a mapping relationship model.

[0066] In the embodiment of the present application, the road safety risk assessment device searches for the road friction coefficient corresponding to the preset weather phenomenon in each preset time period according to the preset mapping relationship. Among them, one preset time period corresponds to one road friction coefficient. In this way, the road friction coefficient of the target road section can be accurately obtained based on the weather forecast phenomenon, providing strong support for road safety risk assessment.

[0067] Another aspect of the embodiments of the present application provides a road safety risk assessment device. Figure 2 The schematic diagram of the structure of a road safety risk assessment provided by the embodiment of the present application is shown as follows: Figure 2 As shown, the road safety risk assessment device 20 may include the following modules.

[0068] The basic road section information acquisition module 21 is used to acquire basic road section information of a target road section, wherein the basic road section information at least includes location information.

[0069] The weather forecast information acquisition module 22 is used to acquire weather forecast information of the target road section within multiple preset time periods based on the location information, and the weather forecast information includes weather forecast phenomena and road visibility.

[0070] The road friction coefficient obtaining module 23 is used to obtain the road friction coefficient of the target road section based on the weather forecast phenomenon.

[0071] The safety risk index obtaining module 24 is used to input basic road section information, road friction coefficient in each preset time period and road visibility into the road section safety risk assessment model to obtain the safety risk index of the target road section in each preset time period.

[0072] In the above embodiment, the basic section information of the target section is obtained to understand the basic situation of the designated section, and the weather forecast information of the target section in multiple preset time periods is obtained based on the location information in the basic section information, so as to obtain the mesoscale weather forecast data in multiple prediction time periods. And the road friction coefficient of the target section is obtained based on the weather forecast phenomenon, so that the key factors of road safety risk assessment can be obtained through the mesoscale weather forecast data. The basic section information, the road friction coefficient in each preset time period and the road visibility are input into the section safety risk assessment model to obtain the safety risk index of the target section in each preset time period, so that the safety risk index of the target section in each preset time period can be accurately assessed in advance through the section safety risk assessment model. In this way, not only can the road safety be assessed in advance, but also the accuracy of the road safety assessment can be improved, providing favorable support for road safety warning.

[0073] In some embodiments, the basic road section information includes at least one of the following: horizontal curve radius, maximum longitudinal slope, vertical curve radius, road surface damage, road safety facilities and sign completeness.

[0074] The safety risk index obtaining module is specifically used to input the horizontal curve radius, maximum longitudinal slope, vertical curve radius, road surface damage, completeness of road safety facilities and signs and signboards, road friction coefficient in each preset time period and road visibility of the target road section into the road section safety risk assessment model to obtain the safety risk index of the target road section in each preset time period.

[0075] In some embodiments, the road section safety risk assessment model is a linear regression prediction model.

[0076] In some embodiments, the road safety risk assessment device 20 may also include a model determination module, which is used to determine whether there is historical accident information on the target road section before inputting basic road section information, road friction coefficient in each preset time period and road visibility into the road section safety risk assessment model to obtain the safety risk index of the target road section in each preset time period. The historical accident information includes the historical accident level, the weather and meteorology of the historical accident, and the road visibility of the historical accident; if so, obtain the road section safety risk assessment model trained based on the historical accident information; if not, determine the preset risk assessment model as the road section safety risk assessment model.

[0077] In some embodiments, the road safety risk assessment device 20 may also include a safety warning module, which is used to input basic road section information, road friction coefficient in each preset time period and road visibility into the road section safety risk assessment model to obtain the safety risk index of the target road section in each preset time period, and then determine whether there is a target safety risk index in the safety risk index in each preset time period that is higher than a preset threshold; if so, the preset time period corresponding to the target safety risk index, weather forecast information and the location information are sent to a third party for safety warning.

[0078] In some embodiments, the road friction coefficient obtaining module 23 is specifically used to obtain the road friction coefficient of the target road section corresponding to the weather forecast phenomenon based on a mapping relationship between the preset weather forecast phenomenon and the road friction coefficient.

[0079] It should be understood that the specific features, operations and details described hereinabove with respect to the method of the present application may also be similarly applied to the device and system of the present application, or vice versa. In addition, each step of the method of the present application described above may be performed by a corresponding component or unit of the device or system of the present application.

[0080] It should be understood that each module / unit of the device of the present application can be implemented in whole or in part by software, hardware, firmware or a combination thereof. Each module / unit can be embedded in the processor of the electronic device or independent of the processor in the form of hardware or firmware, or can be stored in the memory of the electronic device in the form of software for the processor to call to perform the operation of each module / unit. Each module / unit can be implemented as an independent component or module, or two or more modules / units can be implemented as a single component or module.

[0081] According to another aspect of the embodiments of the present application, an electronic device is provided. Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown. Figure 3 As shown, the electronic device 30 includes a processor 31 and a memory 32 storing computer program instructions. When the processor 31 executes the computer program instructions, each step of the road safety risk assessment method described above is implemented. The electronic device 30 can be generally a server, a terminal, or any other electronic device with necessary computing and / or processing capabilities.

[0082] In one embodiment, the electronic device 30 may include a processor, a memory, a network interface, a communication interface, etc. connected through a system bus. The processor of the electronic device 30 may be used to provide necessary computing, processing and / or control capabilities. The memory of the electronic device 30 may include a non-volatile storage medium and an internal memory. The non-volatile storage medium may store an operating system, a computer program, etc. The internal memory may provide an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface and the communication interface of the electronic device 30 may be used to connect and communicate with external devices through a network. When the computer program is executed by the processor, the steps of the road safety risk assessment method of the present application are executed.

[0083] Another aspect of the present application provides a computer-readable storage medium, Figure 4 A schematic diagram showing the structure of a computer-readable storage medium provided in an embodiment of the present application is shown as follows: Figure 4 As shown, a computer-readable storage medium 40 stores a computer-executable program 41 , wherein the computer-executable program 41 implements the steps of the above-mentioned road safety risk assessment method when executed by a processor.

[0084] Another aspect of the present application provides a computer program product, Figure 5 A schematic diagram showing the structure of a computer program product provided by an embodiment of the present application is shown in FIG. Figure 5 As shown, the computer program product 50 includes computer executable instructions 51, wherein when the computer executable instructions 51 are executed by a processor, the steps of the road safety risk assessment method provided in any of the above embodiments are implemented.

[0085] Those skilled in the art will appreciate that the method steps of the present application can be performed by instructing related hardware such as the electronic device 30 or a processor through a computer program, and the computer program can be stored in a non-temporary computer-readable storage medium, and the computer program causes the steps of the present application to be executed when it is executed. Depending on the circumstances, any reference to memory, storage, or other media herein may include non-volatile or volatile memory. Examples of non-volatile memory include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid state disk, etc. Examples of volatile memory include random access memory (RAM), external cache memory, etc.

[0086] The various technical features described above can be combined arbitrarily. Although all possible combinations of these technical features are not described, any combination of these technical features should be considered to be covered by this specification as long as there is no contradiction in such combination.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A road safety risk assessment method, characterized in that: include: Acquire basic section information of the target section, wherein the basic section information at least includes location information; Acquiring weather forecast information of the target road section within a plurality of preset time periods based on the location information, wherein the weather forecast information includes weather forecast phenomena and road visibility; Obtaining a road friction coefficient of the target road section based on the weather forecast phenomenon; The basic road section information, the road friction coefficient in each preset time period, and the road visibility are input into a road section safety risk assessment model to obtain a safety risk index of the target road section in each preset time period.

2. The method according to claim 1, characterized in that: Basic road section information includes at least one of the following: horizontal curve radius, maximum longitudinal slope, vertical curve radius, road surface damage, road safety facilities and signs and signboards completeness; The step of inputting the basic road section information, the road friction coefficient in each preset time period, and the road visibility into the road section safety risk assessment model to obtain the safety risk index of the target road section in each preset time period includes: The horizontal curve radius, maximum longitudinal slope, vertical curve radius, road surface damage, completeness of road safety facilities and signs, road friction coefficient in each preset time period, and road visibility of the target road section are input into the road section safety risk assessment model to obtain the safety risk index of the target road section in each preset time period.

3. The method according to claim 1, characterized in that The road section safety risk assessment model is a linear regression prediction model.

4. The method according to any one of claims 1 to 3, characterized in that: Before inputting the basic road section information, the road friction coefficient in each preset time period, and the road visibility into the road section safety risk assessment model to obtain the safety risk index of the target road section in each preset time period, the method further includes: Determine whether there is historical accident information on the target road section, wherein the historical accident information includes the historical accident level, the weather and meteorological conditions of the historical accident, and the road visibility of the historical accident; If so, obtaining a road section safety risk assessment model trained based on the historical accident information; If it does not exist, the preset risk assessment model will be determined as the road section safety risk assessment model.

5. The method according to claim 1, characterized in that After inputting the basic road section information, the road friction coefficient in each preset time period, and the road visibility into the road section safety risk assessment model to obtain the safety risk index of the target road section in each preset time period, the method further includes: Determine whether there is a target security risk index higher than a preset threshold value among the security risk indexes in each preset time period; If so, the preset time period corresponding to the target safety risk index, weather forecast information and the location information are sent to a third party for safety warning.

6. The method according to claim 1, characterized in that The road friction coefficient of the target road section obtained based on the weather forecast phenomenon includes: Based on a preset mapping relationship between the weather forecast phenomenon and the road friction coefficient, the road friction coefficient of the target road section corresponding to the weather forecast phenomenon is obtained.

7. A road safety risk assessment device, characterized in that: include: A basic road section information acquisition module, used to acquire basic road section information of a target road section, wherein the basic road section information at least includes location information; A weather forecast information acquisition module, used to acquire weather forecast information of a target road section within a plurality of preset time periods based on the location information, wherein the weather forecast information includes weather forecast phenomena and road visibility; A road friction coefficient obtaining module, used for obtaining the road friction coefficient of the target road section based on the weather forecast phenomenon; The safety risk index obtaining module is used to input the basic road section information, the road friction coefficient in each preset time period and the road visibility into the road section safety risk assessment model to obtain the safety risk index of the target road section in each preset time period.

8. An electronic device, characterized in that: The electronic device includes a processor and a memory storing computer program instructions, wherein the computer program instructions, when executed by the processor, implement the steps of the road safety risk assessment method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer-executable program, wherein when the computer-executable program is executed by a processor, the steps of the road safety risk assessment method according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises computer executable instructions, wherein when the computer executable instructions are executed by a processor, the steps of the road safety risk assessment method according to any one of claims 1 to 6 are implemented.

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