Method and device for determining road condition information, non-volatile storage medium, processor

Abstract

The present application discloses a method and apparatus for determining road condition information, a non-volatile storage medium, and a processor. Among them, the method includes: obtaining road condition information from a target object, where the road condition information includes: information about the starting point and the destination; when it is determined that there is a target road condition on the target driving path, determining a target section in the target driving path where the target road condition exists, where the target driving path is a driving path including the starting point and the destination; obtaining a road monitoring video of the target section; and sending the road monitoring video to the target object. The present application solves the technical problem of emotional anxiety and even traffic accidents caused by the inability of traffic participants to intuitively and conveniently understand the actual situation of road congestion.

Description

Technical Field

[0001] This application relates to the technical field of vehicle networking. Specifically, it relates to a method and device for determining road condition information, a non-volatile storage medium, and a processor. Background Art

[0002] In recent years, the number of motor vehicles in possession has continued to grow at a high level. Despite the continuous advancement of road network construction, the traffic pressure in cities is relatively high, especially in large and medium-sized cities, where traffic congestion often occurs. After traffic congestion occurs, as the congestion time prolongs, traffic participants often experience restlessness, which may then lead to behaviors such as cutting in line, conflicts, and even traffic accidents.

[0003] Therefore, during a journey or before departure, traffic participants may need to know the road conditions of the travel route they are taking or the upcoming sections at any time. However, the current road condition display method of navigation software only indicates whether there is congestion on the map, and users cannot intuitively and conveniently understand the actual road conditions (such as congestion situations, congestion reasons, etc.). As a result, traffic participants cannot reasonably formulate or adjust travel plans, and the user experience needs to be improved.

[0004] Currently, the understanding of the actual situation of road congestion only stays at the display of congested sections on the map, and the actual situation of road congestion cannot be intuitively and conveniently understood.

[0005] In response to the above problems, no effective solution has been proposed yet. Summary of the Invention

[0006] The embodiments of this application provide a method and device for determining road condition information, a non-volatile storage medium, and a processor to at least solve the technical problem that traffic participants' restlessness and even traffic accidents occur because they cannot intuitively and conveniently understand the actual situation of road congestion.

[0007] According to one aspect of the embodiments of this application, a method for determining road condition information is provided, including: obtaining road condition information from a target object, where the road condition information includes information about the starting point and information about the destination; when it is determined that there is a target road condition on the target driving path, determining a target section in the target driving path where the target road condition exists, where the target driving path is a driving path including the starting point and the destination; obtaining a road monitoring video of the target section; and sending the road monitoring video to the target object.

[0008] Optionally, determining a target road section with a target road condition in a target driving route includes: obtaining a road condition information layer of the target driving route, where the road condition information layer includes: spatial coordinate information of the target road section and congestion level information of the target road section; performing geospatial grid coding on the spatial coordinate information of the target road section to obtain a first spatial grid coding corresponding to the target road section; superimposing the first spatial grid coding and a second spatial grid coding corresponding to the road network model to determine the spatial grid coding range of the target road section in the second spatial grid coding.

[0009] Optionally, before superimposing the first spatial grid coding and the second spatial grid coding corresponding to the road network model, the above method further includes: performing geospatial grid coding on the road network model to obtain the second spatial grid coding.

[0010] Optionally, obtaining a road monitoring video of the target road section includes: retrieving video monitoring devices installed within the spatial grid coding range corresponding to the target road section; obtaining the monitoring videos of the video monitoring devices, and using the monitoring videos as the road monitoring video of the target road section.

[0011] Optionally, retrieving video monitoring devices installed within the spatial grid coding range corresponding to the target road section includes: in the case where video monitoring devices are present within the retrieved spatial grid coding range, marking the positions of the video monitoring devices on the electronic map.

[0012] Optionally, sending the road monitoring video to the target object includes: performing blurring processing on the target information in the road monitoring video to obtain a processed target road monitoring video, where the target information includes: license plate information and facial image information of the target object; sending the target road monitoring video to the target object.

[0013] Optionally, after obtaining the road condition retrieval information from the target object, the above method further includes: retrieving from the standard place name and address database based on the information of the starting point and the information of the destination to obtain the standard place names and addresses corresponding to the starting point and the destination; determining the target driving route according to the standard place names and addresses corresponding to the starting point and the destination.

[0014] According to another aspect of the embodiments of the present application, there is also provided a device for determining road condition information, including: a first acquisition module, configured to acquire road condition information from a target object, where the road condition information includes: information of a starting point and information of a destination; a determination module, configured to determine a target road section with a target road condition in the target driving route when it is determined that there is a target road condition on the target driving route, where the target driving route is a driving route including the starting point and the destination; a second acquisition module, configured to acquire a road monitoring video of the target road section; a sending module, configured to send the road monitoring video to the target object.

[0015] According to another aspect of the embodiments of the present application, a non-volatile storage medium is further provided. The storage medium includes a stored program, wherein when the program runs, it controls the device where the storage medium is located to execute the above method for determining road condition information.

[0016] According to another aspect of the embodiments of the present application, a processor is further provided. The processor is used to run a program, wherein when the program runs, it executes the above method for determining road condition information.

[0017] In the embodiments of the present application, road condition information from a target object is acquired, wherein the road condition information includes: information of the starting point and information of the destination; when it is determined that there is a target road condition on the target driving path, a target section with the target road condition in the target driving path is determined, wherein the target driving path is a driving path including the starting point and the destination; the road monitoring video of the target section is acquired; and the road monitoring video is sent to the target object. By determining the target section with a congested road condition in the target driving path, acquiring the target section and the road monitoring video, and sending the road monitoring video to the target object, the technical effect that traffic participants can view the actual condition of road congestion is achieved, and further the technical problem of emotional anxiety and even traffic accidents caused by traffic participants being unable to intuitively and conveniently understand the actual condition of road congestion is solved. Description of the Drawings

[0018] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation to the present application. In the drawings:

[0019] Figure 1 is a flowchart of a method for determining road condition information according to an embodiment of the present application;

[0020] Figure 2 is a flowchart of another method for determining road condition information according to an embodiment of the present application;

[0021] Figure 3 is a flowchart of another method for determining road condition information according to an embodiment of the present application;

[0022] Figure 4 is a structural diagram of a device for determining road condition information according to an embodiment of the present application. Detailed Embodiments

[0023] To enable those skilled in the art to better understand the solution of this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts shall fall within the protection scope of this application.

[0024] It should be noted that the terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of this application described here can be implemented in an order different from those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0025] According to an embodiment of this application, a method embodiment for determining road condition information is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order from that here.

[0026] Figure 1 is a flowchart of a method for determining road condition information according to an embodiment of this application. As Figure 1 shown, the method includes the following steps:

[0027] Step S102, obtain road condition information from a target object, where the road condition information includes: information about the starting point and information about the destination;

[0028] According to an optional embodiment of this application, the target object refers to a traffic participant who plans to travel or has already traveled. The target object inputs the names of the starting point and the destination through an electronic map running on a terminal device.

[0029] In this step, based on the starting point information and destination information entered by the traffic participant, a search is performed in the standard place name and address database, and the standard place name and address corresponding to the starting point information and destination information can be obtained. After obtaining the marked place name and address corresponding to the starting point information and destination information, the corresponding geographical space grid code can be further obtained.

[0030] Geospatial grid coding is the process of converting the spatial location information represented by a geographic grid from one form to another. A geospatial grid is one of the important tools for the organization, management, analysis, and application of spatial information in the big data era. Coding is the specific manifestation of a geospatial grid. It can not only be used for the implementation of computer languages and efficient calculations but is also a geographical location identifier in location-based services and a technical support means for modern information exchange and information sharing. Geospatial grid coding assigns a globally unique geographical identifier to regions ranging from the entire Earth down to the centimeter level. Through coding, a computer can identify various location elements of the geographical space represented by the geospatial grid and further achieve efficient calculations based on the coding. The functions of geospatial grid coding mainly include two aspects. One is to symbolize the theory of the geographical network and form a form that can be conveniently used in daily public life. The theory of the geospatial grid needs to be intuitively expressed through coding for easy public memory, identification, recording, and application. The other function is to establish a digital space of spatial geographical grids suitable for computer representation and processing. Through geospatial grid coding, it is possible to achieve efficient coded calculations for spatial analysis.

[0031] Step S104, when it is determined that there is a target road condition on the target driving path, determine the target section of the target driving path where the target road condition exists, where the target driving path is a driving path including a starting point and a destination.

[0032] As an optional embodiment of the present application, the above-mentioned target road condition is a congestion road condition, or it can be other road conditions such as an accident road condition.

[0033] According to another optional embodiment of the present application, the target driving path is the optimal driving path for a traffic participant selected from options such as the shortest required time and the least required cost between the starting point and the destination provided by the traffic participant through an electronic map.

[0034] Step S106, obtain the road monitoring video of the target section.

[0035] In some optional embodiments of the present application, the target section is a section where congestion occurs within the section from the starting point to the destination. Expand the range of the target section one to three kilometers in the directions of the congestion starting point and the end point to obtain the target section after the expanded range. Then, retrieve the video monitoring devices installed within the corresponding spatial grid coding range on the target section after the expanded range. After retrieving the video monitoring devices, mark the locations of the video monitoring devices on the electronic map.

[0036] Step S108, send the road monitoring video to the target object.

[0037] Through the above method, by determining the target road section with congested traffic conditions in the target driving path, obtaining the target road section and the road monitoring video, and sending the road monitoring video to the target object, the technical effect that traffic participants can view the actual situation of road congestion is achieved. This relieves the anxiety of traffic participants facing congestion and improves the travel efficiency of traffic participants.

[0038] In some alternative embodiments of the present application, to execute step S104 to determine the target road section with congested traffic conditions in the target driving path, it can be achieved by the following method: Obtain the traffic condition information layer of the target driving path, where the traffic condition information layer includes: the spatial coordinate information of the target road section and the congestion level information of the target road section; perform geospatial grid coding on the spatial coordinate information of the target road section to obtain the first spatial grid coding corresponding to the target road section; superimpose the first spatial grid coding and the second spatial grid coding corresponding to the road network model to determine the spatial grid coding range of the target road section in the second spatial grid coding.

[0039] According to another alternative embodiment of the present application, first import the traffic condition information layer on the driving path specified by the traffic participant. The traffic condition layer contains information such as congested road sections, the spatial coordinate information covered by the congested road sections, and congestion levels (different congestion levels indicate different degrees of vehicle congestion on the road). Secondly, perform geospatial grid coding on the spatial coordinate information on the specified driving path to obtain the first spatial grid coding; thirdly, perform geospatial grid coding on the road network structure model as well to obtain the second spatial grid coding; finally, superimpose the first spatial grid coding and the second spatial grid coding together, and determine the range of the spatial grid coding of the target road section with congested traffic conditions in the second spatial grid coding through the superimposed content.

[0040] As an alternative embodiment, the encoding technique for geospatial grid encoding of the spatial coordinate information of the target road section may adopt Beidou grid encoding or GeoHash encoding. Among them, Beidou grid encoding is a discretized and multi-scale regional location identification system developed based on the theory of geospatial subdivision of the Earth. It can assign a globally unique integer encoding to any grid of various sizes in the Earth's space from the geocenter to 60,000 kilometers above the ground, with a maximum accuracy of 1.5 centimeters, and can establish an internal mutual association with any entity object and various different data within the same regional scope. GeoHash encoding is a general geocoding algorithm that can encode geographical longitude and latitude coordinates into short strings composed of letters and numbers. It has the following characteristics: First, it is a hierarchical spatial data structure, which can divide geographical locations with rectangular grids, and the geocoding within the same grid is the same; second, when the encoding length is long enough, it can represent geographical location coordinates with any precision; finally, the longer the encoding prefix match, the closer the geographical locations are. GeoHash encoding uses the dichotomy method to continuously narrow the intervals of longitude and latitude for binary encoding, and finally cross-combines the odd and even bits of the encodings generated by longitude and latitude respectively, and then represents them with alphanumeric characters.

[0041] In some alternative embodiments of the present application, before superimposing the first spatial grid encoding and the second spatial grid encoding corresponding to the road network model, the following steps are further included: performing geospatial grid encoding on the road network model to obtain the second spatial grid encoding.

[0042] In the embodiments of the present application, the encoding technique for geospatial grid encoding of the road network model is the same as the encoding technique for geospatial grid encoding of the spatial coordinate information of the target road section, and Beidou grid encoding or GeoHash encoding is also adopted.

[0043] Through the above steps, a spatial three-dimensional grid model in which the spatial coordinate information of the target road section and the road network model are mutually integrated and associated is constructed, realizing the conversion of three-dimensional geospatial information into one-dimensional spatial encoding information. The one-dimensional spatial encoding information can greatly improve the retrieval efficiency, enabling traffic participants to more quickly understand the congestion status of the target road section.

[0044] According to another alternative embodiment of the present application, obtaining the road monitoring video of the target road section includes the following steps: retrieving the video monitoring devices installed within the range of the spatial grid encoding corresponding to the target road section; obtaining the monitoring videos of the video monitoring devices and using the monitoring videos as the road monitoring videos of the target road section.

[0045] In some alternative embodiments of the present application, retrieving video surveillance devices installed within the spatial grid coding range corresponding to the target road section can be achieved through the following method: when video surveillance devices are found within the spatial grid coding range, mark the positions of the video surveillance devices on the electronic map.

[0046] Based on the positions of the video surveillance devices marked in the electronic map of their terminal devices, traffic participants can intuitively understand the locations where traffic congestion occurs and choose whether to view the video surveillance within the congestion range and view the video surveillance at a specific location within the congestion range.

[0047] Through the above steps, traffic participants can understand in detail the reasons for the congestion, providing well-founded support for the subsequent driving decisions of traffic participants and avoiding a lot of unnecessary time waste and anxiety.

[0048] In some alternative embodiments of the present application, sending the road surveillance video to the target object is achieved through the following method: performing blurring processing on the target information in the road surveillance video to obtain the processed target road surveillance video, where the target information includes license plate information and facial image information of the target object.

[0049] In this step, sensitive information such as vehicle license plates and facial image information of traffic participants in the road surveillance video is blurred and then sent to traffic participants.

[0050] Through the above steps, traffic participants can not only understand the congestion situation in real time and reduce the anxiety caused by congestion, but also protect the personal privacy of traffic participants.

[0051] According to another alternative embodiment of the present application, after obtaining the road condition retrieval information from the target object, the following methods are further included: retrieving from the standard geographical name address library based on the information of the starting point and the destination to obtain the standard geographical names corresponding to the starting point and the destination; determining the target driving route according to the standard geographical names corresponding to the starting point and the destination.

[0052] Through the above steps, combined with the road congestion situation, it is possible to provide traffic participants with a convenient and effective route planning from the starting point to the destination.

[0053] Figure 2 It is a flowchart of another method for determining road condition information according to an embodiment of the present application, as Figure 2 shown, and the method includes the following steps:

[0054] Step S202, performing geographical spatial grid coding on the road network model.

[0055] According to an alternative embodiment of the present application, the geographical space of the road network model is encoded with a globally unique geographical space code, and a spatial three-dimensional grid model integrating and associating the road network model, standard place names and addresses, and geographical space codes is constructed.

[0056] Through the above steps, the geographical space range of the road network is grid-coded. For address matching, path planning, video retrieval, etc., retrieval is performed through one-dimensional coding information, which can greatly improve the retrieval efficiency.

[0057] Step S204, standard place name and address matching.

[0058] According to another alternative embodiment of the present application, based on the starting point and destination information. The standard place name and address are retrieved in the standard place name and address database, and their spatial grid codes are obtained respectively.

[0059] Step S206, travel path planning.

[0060] In some alternative embodiments of the present application, travel path planning is performed based on the spatial grid code. For example, the travel path can include path planning with the shortest distance, path planning with the least time consumption, etc.

[0061] Step S208, import traffic condition information and congested geographical space segmentation.

[0062] In some alternative embodiments of the present application, traffic conditions are monitored based on roadside devices such as video surveillance cameras and lidar to obtain a traffic condition information layer, or external map traffic condition layers such as Amap, Baidu, and Tencent can be directly introduced; the traffic condition layer contains information such as congested sections, spatial coordinate information covered by the congested sections, and congestion levels. The spatial coordinate information of the congested sections is extracted, and based on the elevation information such as longitude and latitude in the coordinates, spatial geographical coding is performed based on the Beidou grid code, etc. Since the road network model has been spatially grid-coded, the road network model and the traffic condition layer that are spatially divided using the same coding method can be superimposed. Thus, the congestion range is determined in the three-dimensional grid space, and the superimposed display of the congested sections is realized.

[0063] Step S210, monitoring video retrieval within the area.

[0064] In some alternative embodiments of the present application, the geospatial grid codes of the starting point and the ending point of the congested section are obtained. Considering the visible range of video surveillance, the range of the congested section is expanded one kilometer in each direction towards the starting point and the ending point of the congestion, and the video retrieval range of the congested section is determined. According to the spatial codes of the video retrieval range of the congested section, the installed video surveillance devices within the coded range are retrieved. If a viewable surveillance device is found within the congested space range, the information point (Point of Interest, POI) of the device is lit at the corresponding position on the map, indicating that there is a congested road condition on the path of travel or the planned route, and there is an available video surveillance device, and the video stream can be called up for viewing.

[0065] Step S212, video blurring processing.

[0066] According to another alternative embodiment of the present application, sensitive information such as vehicle license plates and faces in the video stream is blurred and then distributed externally.

[0067] Step S214, video distribution.

[0068] Through the above steps, it can help traffic participants have a real-time and intuitive understanding of the congestion situation when congestion occurs, and can also help traffic participants reasonably plan travel modes, travel plans, and travel routes, and have an intuitive understanding of the road conditions of the travel route in advance.

[0069] Figure 3 It is a flowchart of another method for determining road condition information according to an embodiment of the present application. As Figure 3 shown, the method includes the following steps:

[0070] Step S302, road condition retrieval.

[0071] According to an alternative embodiment of the present application, traffic participants can retrieve the road conditions of the travel section by inputting the information of the starting point and the destination in voice or text in the electronic map on the mobile terminal device.

[0072] Step S304, prompt: The road ahead is congested. Do you want to view the road condition monitoring video?

[0073] According to another alternative embodiment of the present application, after retrieving a congested section and there is a viewable surveillance device within the congested section, the information point (Point of Interest, POI) of the surveillance device is lit at the corresponding position on the electronic map, and traffic participants are prompted on the electronic map: The road ahead is congested. Do you want to view the road condition monitoring video?

[0074] Step S306, processed video push.

[0075] According to another alternative embodiment of the present application, sensitive information such as vehicle license plates and facial image information of traffic participants in road monitoring videos is blurred and then sent to traffic participants. Traffic participants can learn the specific reasons for road congestion through the video, and judge whether to continue on the original route or change to a new route that is farther but has no congestion. Even if traffic participants cannot change the original route, by watching the monitoring video of the congested section, it can greatly relieve the anxiety of traffic participants and avoid some traffic accidents caused by anxiety.

[0076] Figure 4 is a structural diagram of a device for determining road condition information according to an embodiment of the present application, as Figure 4 shown, the device includes:

[0077] A first acquisition module 40, configured to acquire road condition information from a target object, where the road condition information includes: information about a starting point and information about a destination;

[0078] A determination module 42, configured to determine a target section with a congested road condition in the target driving route when it is determined that there is a congested road condition on the target driving route, where the target driving route is a driving route including the starting point and the destination;

[0079] A second acquisition module 44, configured to acquire a road monitoring video of the target section;

[0080] A sending module 46, configured to send the road monitoring video to the target object.

[0081] It should be noted that Figure 4 The preferred implementation manners of the illustrated embodiments can refer to Figure 1 the relevant descriptions of the illustrated embodiments, and will not be elaborated here.

[0082] The embodiment of the present application further provides a non-volatile storage medium, and the non-volatile storage medium includes a stored program, where when the program runs, it controls the device where the storage medium is located to execute the above road condition information determination method.

[0083] A program for the non-volatile storage medium to execute the following functions: acquiring road condition information from a target object, where the road condition information includes: information about a starting point and information about a destination; determining a target section with a target road condition in the target driving route when it is determined that there is a target road condition on the target driving route, where the target driving route is a driving route including the starting point and the destination; acquiring a road monitoring video of the target section; sending the road monitoring video to the target object.

[0084] The embodiment of the present application further provides a processor, and the processor is used to run a program, where when the program runs, it executes the above road condition information determination method.

[0085] The processor is used to run a program that performs the following functions: obtaining road condition information from a target object, where the road condition information includes: information about the starting point and information about the destination; when it is determined that there is a target road condition on the target driving path, determining a target section in the target driving path where the target road condition exists, where the target driving path is a driving path including the starting point and the destination; obtaining a road monitoring video of the target section; and sending the road monitoring video to the target object.

[0086] The serial numbers of the embodiments of the present application above are only for description and do not represent the superiority or inferiority of the embodiments.

[0087] In the above embodiments of the present application, the descriptions of the respective embodiments have their own emphases. For parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0088] In several embodiments provided by the present application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only illustrative. For example, the division of the units can be a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of units or modules can be in an electrical or other form.

[0089] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0090] In addition, the functional units in each embodiment of the present application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0091] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the related technology, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, read-only memories (ROMs), random access memories (RAMs), mobile hard disks, magnetic disks, or optical discs.

[0092] The foregoing are only the preferred embodiments of this application. It should be noted that for those of ordinary skill in the art, without departing from the principle of this application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of this application.

Claims

1. A method for determining road condition information, characterized in that, it includes: Obtain road condition information from a target object, where the road condition information includes: information about the starting point and information about the destination; When it is determined that there is a target road condition on the target driving path, determine the target section with the target road condition in the target driving path, including: obtaining a road condition information layer of the target driving path, where the road condition information layer includes: spatial coordinate information of the target section and congestion level information of the target section; performing geospatial grid coding on the spatial coordinate information of the target section to obtain a first spatial grid coding corresponding to the target section; performing geospatial grid coding on the road network model to obtain a second spatial grid coding; superimposing the first spatial grid coding and the second spatial grid coding corresponding to the road network model to determine the spatial grid coding range of the target section in the second spatial grid coding, where the target driving path is a driving path including the starting point and the destination; Obtain the road monitoring video of the target section; Send the road monitoring video to the target object.

2. The method according to claim 1, characterized in that, Obtaining the road monitoring video of the target section includes: Retrieve video monitoring devices installed within the spatial grid coding range corresponding to the target section; Obtain the monitoring video of the video monitoring device and use the monitoring video as the road monitoring video of the target section.

3. The method according to claim 2, characterized in that, Retrieving video monitoring devices installed within the spatial grid coding range corresponding to the target section includes: When it is retrieved that there is a video monitoring device within the spatial grid coding range, mark the position of the video monitoring device on the electronic map.

4. The method according to claim 1, characterized in that, Sending the road monitoring video to the target object includes: Performing blurring processing on the target information in the road monitoring video to obtain a processed target road monitoring video, where the target information includes: license plate information and facial image information of the target object; Send the target road monitoring video to the target object.

5. The method according to claim 1, characterized in that, After obtaining the road condition retrieval information from the target object, the method further includes: Retrieving from a standard place name and address database based on the information about the starting point and the information about the destination to obtain the standard place names and addresses corresponding to the starting point and the destination; Determine the target driving path according to the standard place names and addresses corresponding to the starting point and the destination.

6. A device for determining road condition information, characterized in that, it includes: A first acquisition module for obtaining road condition information from a target object, where the road condition information includes: information about the starting point and information about the destination; A determination module, configured to determine a target road section with the target road condition in the target driving path when it is determined that there is a target road condition on the target driving path, including: obtaining a road condition information layer of the target driving path, where the road condition information layer includes: spatial coordinate information of the target road section and congestion level information of the target road section; performing geospatial grid coding on the spatial coordinate information of the target road section to obtain a first spatial grid coding corresponding to the target road section; performing geospatial grid coding on a road network model to obtain a second spatial grid coding; superimposing the first spatial grid coding and the second spatial grid coding corresponding to the road network model to determine a spatial grid coding range of the target road section in the second spatial grid coding, where the target driving path is a driving path including the starting point and the destination. A second acquisition module, configured to acquire a road monitoring video of the target road section. A sending module, configured to send the road monitoring video to the target object.

7. A non-volatile storage medium characterized in that the non-volatile storage medium includes a stored program, where, when the program runs, it controls the device where the non-volatile storage medium is located to execute the method for determining road condition information according to any one of claims 1 to 5.

8. A processor characterized in that the processor is used to run a program stored in a memory, where, when the program runs, it executes the method for determining road condition information according to any one of claims 1 to 5.

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