CN116416790A - Road prompt information generation method, broadcasting method and device - Google Patents

Road prompt information generation method, broadcasting method and device Download PDF

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Publication number
CN116416790A
CN116416790A CN202211575346.5A CN202211575346A CN116416790A CN 116416790 A CN116416790 A CN 116416790A CN 202211575346 A CN202211575346 A CN 202211575346A CN 116416790 A CN116416790 A CN 116416790A
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road
information
road section
target
fingerprint table
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徐攀登
黄晓婧
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Alibaba Cloud Computing Ltd
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Alibaba Cloud Computing Ltd
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125—Traffic data processing
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
    • G08G1/0141—Measuring and analyzing of parameters relative to traffic conditions for specific applications for traffic information dissemination
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/091—Traffic information broadcasting

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  • General Physics & Mathematics (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Traffic Control Systems (AREA)

Abstract

The application provides a method for generating road prompt information, a broadcasting method and a device, wherein the method for generating the road prompt information can comprise the following steps: determining the running states of the candidate road sections and the target vehicles according to the information of the target vehicles; the information of the target vehicle includes information detected by a sensor of the target vehicle; determining a target road section from the candidate road sections by using a road section fingerprint table of the candidate road sections; the road section fingerprint table is pre-constructed and is used for representing road section related basic information and road section related risk information of the candidate road sections; and generating road prompt information by utilizing the road fingerprint table and the driving state of the target road. According to the embodiment of the application, the road section coverage of the prompt message can be improved, and the driving safety is optimized.

Description

Road prompt information generation method, broadcasting method and device
Technical Field
The application relates to the technical field of intelligent transportation, in particular to a method for generating road prompt information, a broadcasting method and a device.
Background
In order to reduce the road accident rate and improve the driving safety of the vehicle, a more common way is to play road prompt information to the driver so as to help the driver avoid some risks in advance. In some related technologies, road prompt information may be issued by some designated institutions, limited by regional limitations, and insufficient coverage.
Disclosure of Invention
The embodiment of the application provides a method, a device, an electronic device and a storage medium for generating road prompt information, wherein the method, the device, the electronic device and the storage medium break regional limitation by utilizing a pre-constructed road section fingerprint table, and the road section coverage is improved. Road prompt information can be sent to the user to improve driving safety.
In a first aspect, an embodiment of the present application provides a method for generating road prompt information, where the method may include:
determining the running states of the candidate road sections and the target vehicles according to the information of the target vehicles; the information of the target vehicle includes information detected by a sensor of the target vehicle;
determining a target road section from the candidate road sections by using a road section fingerprint table of the candidate road sections; the road section fingerprint table is pre-constructed and is used for representing road section related basic information and road section related risk information of the candidate road sections;
and generating road prompt information by utilizing the road fingerprint table and the driving state of the target road.
In a second aspect, an embodiment of the present application provides a method for broadcasting a road prompt information, where the method may include:
uploading information of the vehicle; the information of the vehicle includes information detected by a sensor of the vehicle;
broadcasting the road prompt information generated by the received information of the response vehicle; the road prompt information is generated by utilizing a road section fingerprint table and a driving state of a target road section; the target road section is determined from the candidate road section by using a road section fingerprint table of the candidate road section; the road section fingerprint table is pre-constructed and is used for representing road section related basic information and road section related risk information of the candidate road sections; the candidate road segments and the running state are determined based on the information of the target vehicle.
In a third aspect, an embodiment of the present application provides a device for generating road prompt information, where the device may include:
the basic information determining module is used for determining the running states of the candidate road sections and the target vehicle according to the information of the target vehicle; the information of the target vehicle includes information detected by a sensor of the target vehicle;
the target road section determining module is used for determining a target road section from the candidate road sections by utilizing a road section fingerprint table of the candidate road sections; the road section fingerprint table is pre-constructed and is used for representing road section related basic information and road section related risk information of the candidate road sections;
and the road prompt information generation module is used for generating the road prompt information by utilizing the road section fingerprint table and the driving state of the target road section.
In a fourth aspect, an embodiment of the present application provides a broadcasting device for road prompt information, where the device may include:
the vehicle information uploading module is used for uploading the information of the vehicle; the information of the vehicle includes information detected by a sensor of the vehicle;
the road prompt information broadcasting module is used for broadcasting the received road prompt information generated by responding to the information of the vehicle; the road prompt information is generated by utilizing a road section fingerprint table and a driving state of a target road section; the target road section is determined from the candidate road section by using a road section fingerprint table of the candidate road section; the road section fingerprint table is pre-constructed and is used for representing road section related basic information and road section related risk information of the candidate road sections; the candidate road segments and the running state are determined based on the information of the target vehicle.
In a fifth aspect, embodiments of the present application provide an electronic device including a memory, a processor, and a computer program stored on the memory, the processor implementing the method of any one of the above when the computer program is executed.
In a sixth aspect, embodiments of the present application provide a computer readable storage medium having a computer program stored therein, the computer program implementing a method according to any one of the above when executed by a processor.
Compared with the prior art, the application has the following advantages:
according to the method and the device, the road section fingerprint is generated in an off-line pre-construction mode, so that road sections with more areas can be covered, and the regional limitation is broken. In addition, when the road section fingerprint table is acquired, the road section fingerprint of the adjacent position can be acquired based on the current position of the vehicle, and the response speed is faster. Finally, the method includes the steps of. Because the road section fingerprint contains the road section related risk information of the target road section, the generation of the prompt information is simpler and more convenient, and the calculation resource is saved.
The foregoing description is merely an overview of the technical solutions of the present application, and in order to make the technical means of the present application more clearly understood, it is possible to implement the present application according to the content of the present specification, and in order to make the above and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
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In the drawings, the same reference numerals refer to the same or similar parts or elements throughout the several views unless otherwise specified. The figures are not necessarily drawn to scale. It is appreciated that these drawings depict only some embodiments according to the application and are not to be considered limiting of its scope.
Fig. 1 is a schematic view of a scene based on an image processing scheme provided in the present application;
FIG. 2 is a flowchart of a method for generating road prompt information according to an embodiment of the present application;
FIG. 3 is a logic diagram of generating road hint information according to an embodiment of the present application;
FIG. 4 is a flowchart of a method for broadcasting road prompt information according to an embodiment of the present application;
fig. 5 is a block diagram of a road prompt generation device according to an embodiment of the present application;
fig. 6 is a block diagram of a road prompt broadcasting device according to an embodiment of the present application; and
fig. 7 is a block diagram of an electronic device used to implement an embodiment of the present application.
Detailed Description
Hereinafter, only certain exemplary embodiments are briefly described. As will be recognized by those of skill in the pertinent art, the described embodiments may be modified in various different ways without departing from the spirit or scope of the present application. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not as restrictive.
In order to facilitate understanding of the technical solutions of the embodiments of the present application, the following describes related technologies of the embodiments of the present application. The following related technologies may be optionally combined with the technical solutions of the embodiments of the present application, which all belong to the protection scope of the embodiments of the present application.
The terms referred to in this application are explained first.
Global navigation satellite system (GNSS, global Navigation Satellite System): also known as global satellite navigation systems, are space-based radio navigation positioning systems that provide users with all-weather 3-dimensional coordinates and velocity and time information at any location on the earth's surface or near-earth space.
Road segment (RID): refers to the basic road section in the urban brain.
Digital twinning technique: creating virtual entity of physical entity in digital mode, simulating, verifying, predicting and controlling the whole life cycle process of physical entity by means of history data, real-time data and algorithm model.
Fig. 1 is a schematic diagram of an exemplary application scenario for implementing the method of the embodiments of the present application. The method mainly comprises the steps of marking road section fingerprint data, matching road section fingerprints, vehicle journey, prompting information and the like.
Road segment fingerprints may be used to characterize the condition of the road segment. For example, the name of the road segment, the speed limit condition of the road segment, the type of the road segment, the class of the road segment, etc. may be characterized. For another example, the road segment fingerprint may further include an indication of whether the road segment is a road segment requiring prompting, whether an adjacent road segment of the road segment is a road segment requiring prompting, and so on. Road segment fingerprints are constructed based on the road network base data. The basic data of the Road network can be obtained through a specified database, and the basic data comprises basic Road segments (Base Road), road network topology (Road Graph), traffic network topology relations constructed by using quad trees (quad trees) and the like. Based on the basic data of the road network, the basic information of the road section can be obtained. Based on the basic information, the name of the road segment, the speed limit condition of the road segment, the type of the road segment, the grade of the road segment, and the like can be determined. Based on the difference of basic information between road segments, whether the attribute of the road segments changes or not can be determined, for example, the main road is changed into a ramp, a tunnel is changed into a mountain road, the speed limit is changed into 80 km/h from 120 km/h, and the like. In addition, the road section fingerprint table may also record the road section attribute, and the attribute may include whether the road section is a dangerous road section. Whether a dangerous road section exists in the road section fingerprint table can be determined through accident data or alarm data. For example, road segment matching may be performed based on the start and end points of the accident road segments in the history data, thereby determining the accident-prone road segments. For another example, the alarm condition may be determined based on the alarm section and the alarm indication content, so that the alarm high-speed section may be determined using a box method. Also for example, dangerous road segments may be determined according to road side events or speed limit change conditions, etc., i.e., corresponding road side event matches and road side safety classifications. The above determination process is described in detail later.
The running state of the vehicle may include a running speed of the vehicle, a running duration of the vehicle, a vehicle residence duration, and the like. The data may be acquired based on an onboard global navigation satellite system. In order to improve the matching precision, the collected data of the vehicle-mounted global navigation satellite system can be subjected to denoising processing, for example, the collected data with larger difference with other data can be removed. In addition, the state of the driver may be classified as a running state of the vehicle. During the running of the vehicle, road network matching can be performed based on the running state of the vehicle, and the current road section of the vehicle and the distance from the target road section can be determined. Such as distance from the ramp, distance from the service area, etc.
Based on the travel track of the vehicle, the current road section of the vehicle can be determined in combination with a road network map (RoadMap Load). The determination may be performed using a breadth first algorithm (BFS, breadth First Search). And then, based on the information recorded in the road section fingerprint table of the current road section, when the road section fingerprint table of the current road section or the road section likely to be driven in the future indicates the road section needing prompting, road prompting information can be generated. The road prompt information can comprise a front ramp prompt, a service area prompt, an abnormal parking prompt, an overspeed prompt, a speed limit change prompt and the like. The road prompt information can be played at the vehicle end, so that a driver is prompted to drive safely.
Because the road section fingerprint is generated in an off-line pre-construction mode, road sections of more areas can be covered, and the regional limitation is broken. In addition, when the road section fingerprint is acquired, the road section fingerprint of the nearby position can be acquired based on the current position of the vehicle, and the response speed is faster. Finally, the method includes the steps of. Because the road section fingerprint contains the judgment of whether the target road section is a dangerous road section or whether the road section needs to be prompted, the generation of the prompt information is simpler and more convenient, and the calculation resource is saved.
In addition, the method can be applied to digital twin services based on digital twin technology. For example, a road segment, a building corresponding to the road segment, or the like may be three-dimensionally visualized, thereby reproducing a digitized scene. In addition, based on the digital twin technology, the automobile and intelligent urban road data can be collected, calculated, operated and executed in real time, and the problems encountered by automatic driving are solved through perception, decision and execution. For example, the driving of the vehicle may be simulated, and the cause of the occurrence of the accident when the presentation information is present may be analyzed, so that the driver or the vehicle may be analyzed.
An embodiment of the present application provides a method for generating road prompt information, as shown in fig. 2, which is a flowchart of a method for generating road prompt information in an embodiment of the present application, and corresponding to the first embodiment, may include:
Step S201: determining the running states of the candidate road sections and the target vehicles according to the information of the target vehicles; the information of the target vehicle includes information detected by a sensor of the target vehicle.
The execution body of the embodiment of the application may include a cloud or a car machine. The information of the target vehicle may include information detected by a sensor of the target vehicle. For example, the real-time position and real-time speed of the vehicle obtained by the on-board global navigation satellite system, etc. In addition, the real-time speed of the vehicle can also be obtained through the vehicle instrument panel. The information of the target vehicle may further include a vehicle interior image and a vehicle exterior image acquired by the in-vehicle image acquisition device. The vehicle interior image may include an image of the driver so that it may be determined whether the driver is tired, whether a cell phone is used during driving, or the like, based on an image recognition technique.
From the information of the target vehicle, the running state of the target vehicle can be determined. The driving state may include a real-time position of the target vehicle, a period of time the target vehicle is driving, a period of time the target vehicle is stationary, a vehicle speed during driving of the target vehicle, and the like. Further, the vehicle speed during running may be classified. For example, the time period of speeding, the time period of fast running, the time period of low running, and the like. The overspeed, the fast running, the low speed running, and the like may be defined by a preset vehicle speed threshold value or by a speed limit regulation of a road on which the vehicle is located. Taking the speed limit regulation of the road on which the vehicle is located as an example, for example, the speed limit of a highway is generally 80 to 120 roads/hour, and for traveling exceeding 120 roads/hour, overspeed traveling can be defined. For traveling below 80 highway/hour, low speed travel may be defined. The travel between the two can be classified as fast travel or the like. Different types of information may be acquired in different data type transmissions. For example, the real-time location may be transmitted using a DOUBLE data type, the identification of the target vehicle may be transmitted using a STRING data type, and so on.
In addition, from the information of the target vehicle, a candidate link may also be determined. For example, the traveling direction of the target vehicle may be determined from the traveling locus of the target vehicle. Based on the road network topology structure, the road sections of the target vehicle which are currently running can be connected, and the road sections of which the running process accords with the traffic running rule can be used as candidate road sections. For example, the target vehicle may travel from north to south on an expressway, and a road section of the target vehicle in the south may be used as a candidate road section. For another example, the target vehicle may travel from west to east on an urban road, and the road section of the target vehicle in east may be used as a candidate road section. The number of the candidate road sections is at least one, and can be multiple.
The division of the road segments may be performed according to rules such as the name of the road segment, the length of the road segment, the location of the road segment, and the like. The specific partitioning rules are not described in detail.
Step S202: determining a target road section from the candidate road sections by using a road section fingerprint table of the candidate road sections; the road segment fingerprint table is pre-constructed and used for representing road segment related basic information and road segment related risk information of the candidate road segments.
The pre-constructed link fingerprint table may be used to characterize link-related basic information and link-related risk information of the candidate links. The road segment related basic information may include basic construction information of the road segment, such as a road segment name, a road segment length, a road segment grade, a longitude and latitude of the road segment, and the like. The link-related risk information may be related information that characterizes whether the link has a risk. The infrastructure information may be obtained from a road network related database. Further, different types of information may be transmitted in different data types. For example, the link name may be transmitted using a sting data type, the link length may be transmitted using a big data type, etc.
For road segments with risk, the risk type of the road segment may be further marked. For example, the risk type of the road segment may include an accident-prone road segment, a road segment with changed road properties, and the like. In addition, for each risk type, prompt content or prompt keywords can be correspondingly stored in the road segment fingerprint table.
Determining a target link from the candidate links may first refer to whether the candidate link recorded in the link fingerprint table of the candidate link is a link with risk. If a road segment without risk is attributed, the candidate road segment may be excluded. If a plurality of road segments with risk remain, the target road segment may be determined based on the distance of the target vehicle from the risk road segment.
Step S203: and generating road prompt information by using at least one of a road segment fingerprint table and a driving state of the target road segment.
In one mode, the road prompt information can be generated by directly utilizing prompt contents or prompt keywords stored in the road fingerprint table of the target road. For example, the hint information may include "500 meters ahead as a tunnel segment". "1 km ahead has a road segment leading to a service area". "the front 400 meters is a speed-changing road section, and the speed limit after changing is 40 km/h". The front 300 meters is a ramp entrance, and vehicles are converged in.
In another embodiment, the road guidance information may be generated using the traveling state of the target vehicle. For example, "continuous travel time has exceeded 5 hours, recommended rest", "please avoid using a cell phone during driving", and the like.
In still another mode, the driving state of the target vehicle and the link fingerprint table of the target link can be used for storing prompt contents or prompt keywords to generate the road prompt information. For example, the current running speed of the target vehicle is 100 km/h, and the speed limit of the current road section is 80 km/h, whereby a prompt message "speed limit 80, you have overspeed" can be generated. For another example, the current running state of the target vehicle is stopped and the current road section is a non-stop area, whereby a prompt message "stop is not allowed here" can be generated.
By the scheme, the road section fingerprint table is constructed for different road sections in advance. Based on the road section fingerprint table, road section related basic information, road section related risk information and the like of the road section can be determined, and full coverage of the road network can be achieved. Thus, in the traveling process of the target vehicle, the prompt information for the driver can be generated based on the traveling state of the target vehicle and the link fingerprint table of the current link or the adjacent link communicated with the current link. Since the link fingerprint table is constructed in advance, the delay in generating the hint information can be reduced to less than 2 seconds. In addition, the road section fingerprint table can be adjusted and optimized in real time according to the characteristics constructed under the road section fingerprint table, and the optimization process is more convenient.
In one embodiment, the construction mode of the road section fingerprint table may include:
step S2021: determining road section related basic information and road section related risk information of a current road section, wherein the road section related basic information comprises at least one of road section identification information, road section length information, road section name information, road section type information, road section grade information and adjacent road section information; the road segment related risk information comprises risk type information or risk-free type information; the information with risk type comprises at least one of road side event information and road section attribute change information; the roadside event information includes information of events affecting normal traffic of the road.
The link-related basic information may include at least one of link identification information, link length information, link name information, link type information, link class information, and neighboring link information.
The road section type information is used for representing the type of the road section. The types of the road segments may include a ramp type, a tunnel type, a road type leading to a service area (parking lot), a mountain road type, an interior road type, and the like. The link class information is used to characterize the class of the link. The grade of the road segment may include expressways, primary highways, secondary highways, etc. Correspondingly, roads of different grades or different types have corresponding speed limiting requirements. For example, highway speed limits typically include 120 km/h, 80 km/h, etc.
Road segments without risk may be considered regular road segments. For road segments that are at risk, the risk type of the road segment may be further subdivided. For example, the risk type of the road segment may include a road segment at risk of a road side event or a road segment at risk of a change in the attribute of the road segment, or the like. The risk level of the road side event risk may be higher than the risk level of the road section attribute change risk.
Further, the road sections at risk of the road side event can be further subdivided into road sections at which the road side event is a traffic accident or road maintenance, etc. Road segments at which the road segment attributes change risk may be further subdivided into: and the road condition changing road section is changed according to the road condition, and the road speed is limited.
The accident-prone road sections and the violation-prone road sections can be determined through historical data. The speed limit change road segment may refer to a change in speed limit condition of the current road segment as compared to the adjacent road segment. The road condition change road section may refer to that the current road section is changed from the adjacent road section. The road condition change may include driving from a highway to a primary road, driving from a main road to a ramp, driving from a non-tunnel section to a tunnel section, etc. The road side event occurrence section may refer to a section where a normal driving event is affected. For example, the road section where traffic accident occurs, the road section being maintained, etc. may be mentioned.
Wherein, the determination of accident-prone road segments and violation-prone road segments can depend on historical data. The determination of the speed limit change road segments and the road condition change road segments can depend on road network information. The determination of the road-side event occurring road segment may depend on information issued by a designated institution or on information reported by a vehicle or user traveling to the road segment.
The construction of the road segment fingerprint table of each road segment can be finished on line in advance. Meanwhile, the road section fingerprint table can have the attribute of real-time update and real-time editing. For example, the frequency of information change is low for the determination of accident-prone road segments, offending-prone road segments, speed-limit change road segments, and road condition change road segments, and therefore the frequency of confirmation and adjustment of the road segments is also relatively low. Thus, the updating of the link fingerprint table mainly includes the links where the road side event occurs. In conclusion, the whole calculated amount of the road section fingerprint table is small in updating, and updating of the road section fingerprint table can be completed in time under the condition that a road side event occurs.
Step S2022: and constructing a road section fingerprint table of the current road section by utilizing the road section related basic information and the road section related risk information.
After the road section related basic information and the road section related risk information of the current road section are determined, the road section fingerprint table of the current road section can be generated based on the road section related basic information and the road section related risk information. And obtaining a road section fingerprint table of each road section in the road network by using the topological relation among the road sections.
Through the process, the road section fingerprint table of the road section can be obtained in a pre-constructed mode. Since link-related basic information and link-related risk information of the link, etc. can be stored in the link fingerprint table. The link fingerprint table can be used for quick generation of prompt information when driving to a link with risk. And based on the road section fingerprint table, the updatable attribute can be edited, so that the update flow of the prompt information can be simplified.
In one embodiment, in the case where the link-related risk information includes the road side event information, the construction method of the link fingerprint table referred to in step S202 may include:
step S20211: and determining a starting area and a termination area of the road side event according to the received information of the road side event.
The information of the road side event can be issued by a designated organization, can be uploaded by vehicles or pedestrians, and the like. Based on the analysis of the information of the roadside event, the start point and the end point of the roadside event can be determined. For example, the information of a roadside event is "an accident occurs in the north-south direction of the XX route". Based on this, the south end of the XX road may be the start of the roadside event and the north end of the XX road may be the end of the roadside event. For another example, the information of the roadside event is "congestion occurs at the exit of XX parking lot". Based on this, the entrance of the XX parking lot may be the start of the roadside event and the exit of the XX parking lot may be the end of the roadside event.
Further, the matching accuracy is improved subsequently, the range of the starting point and the end point can be expanded, and the points can be expanded into areas. For example, a nine-square is constructed centering on the starting point. The region corresponding to the nine boxes can be used as the initial region of the road side event. Similarly, a nine-square lattice can be constructed with the end point as the center.
The start and end regions of the roadside event may be in encoded form. For example, the start region and the end region of the roadside event may be address coded (Geohash coded). The address coding is a position coding method, and can code two-dimensional longitude and latitude data into a character string. For the position with missing longitude and latitude data, interpolation calculation can be performed by using the longitude and latitude data of the adjacent position, so as to obtain longitude and latitude data for filling.
Step S20212: a first set of road segments matching the starting region and a second set of road segments matching the ending region are determined.
And matching the initial area of the road side event with the locating point of the existing road section by using address coding. In addition, the termination area of the road side event is matched with the anchor point of the existing road section. For selection of an existing road segment, a road segment may be selected that has a distance from the roadside event start region or end region that is less than a corresponding distance threshold. The distance threshold may be 50 meters, 100 meters, 200 meters, etc.
The matching process may include: firstly, determining address codes of all data acquisition points or all data acquisition areas of the existing road section. And comparing the starting area and the ending area of the road side event with the existing road sections respectively. When the comparison result indicates that the overlapping area exists, the road section overlapping with the starting area can be selected into the first road section set, and the road section overlapping with the ending area can be selected into the second road section set.
Step S20213: determining a road section where a road side event occurs by using the first distance and the second distance; the first distance is determined using the distance between the starting region and the road segments comprised in the first set of road segments; the second distance is determined using the distance between the termination area and the road segments comprised in the second set of road segments.
Assuming that the first road segment set includes M road segments, and the second road segment set includes N road segments, wherein N, M is a positive integer not less than 1. From the starting area, the feet are respectively led to M road sections, and M results are obtained. And respectively calculating length units corresponding to the M results. Similarly, from the termination area, feet are respectively drawn to N road sections, and N results are obtained. And respectively calculating the length units corresponding to the N results. Here, the segments in the first set and the second set may be further screened. For example, a length threshold may be set. Illustratively, the length threshold may be 10 meters, 25 meters, 50 meters, etc. And in the first road segment set and the second set, only the road segments with the calculation results not larger than the length threshold value are reserved. In the above example, the M results may all correspond to the first distance, or the result smaller than the length threshold in the M results may be corresponding to the first distance. Correspondingly, the N results may all correspond to the second distance, or the result smaller than the length threshold in the N results may be corresponding to the second distance.
Screening in the finally reserved road sections by using a Dijkstra algorithm, taking the start point and the end point of a road side event as target nodes, taking each positioning point in the reserved road sections as an intermediate node, and selecting the road section with the shortest path as the road section where the road side event occurs.
Step S20214: and associating the road section with the road side event to construct a road section fingerprint table.
The road section with the road side event can be associated with the road side event, so that the construction of the road section fingerprint table of the road section can be realized. Furthermore, the road section can be queried periodically, and the road section fingerprint table of the road section can be updated under the condition that the road side event is over.
Through the process, when the road side event occurs, the construction and updating of the road fingerprint table of the road can be realized in response to the road side event.
In one embodiment, in the case where the link-related risk information includes link attribute change information, the construction method of the link fingerprint table in step S202 may include:
step S20215: determining a risk road section according to the traffic history data; the historical data includes at least one of violation data and traffic accident data.
The traffic history data may be traffic accident data, violation data, etc. that have passed a period of time. Traffic accidents caused by driving or road section change can be further subdivided according to the cause of the traffic accidents. For example, traffic accidents caused by driving may include accidents that occur during driving due to the driver using a mobile phone or operating the mobile phone with a lack of concentration. The traffic accident caused by the change of the road section may be a merging accident caused by the narrowing of the road section, or a scratch accident caused by the exit or entrance of the road exiting or entering the vehicle, etc.
In case the number of traffic accidents and/or the number of violations exceeds a certain amount, the current road section may be determined as a risk road section.
Step S20216: and determining the road section attribute change information according to the starting point and the ending point of the risk road section.
And matching with the existing road section according to the starting point and the ending point of the risk road section. Matching the risk road segments into existing road segments. Based on this, the link attribute change information for updating the link fingerprint table of the existing link that is successfully matched can be generated.
Step S20217: and associating the risk road segments with the road segment attribute change information to construct a road segment fingerprint table.
Based on the road segment attribute change information, the road segment fingerprint table of the existing road segment successfully matched can be updated. For example, a risk section is matched to an XX section in an existing section. Thereby generating link attribute change information for updating the link fingerprint table of the XX link. And associating the XX road segment with the road segment attribute change information to complete updating of the road segment fingerprint table. For example, in the updated link fingerprint table of the XX link, "accident-prone links" or "accident-prone links due to narrowing of links" or the like may be added.
In one embodiment, in the case where the link-related risk information includes link attribute change information, the construction method of the link fingerprint table referred to in step S2021 may include:
step S20218: and comparing the acquired road section related basic information of the current road section with road section related basic information of the adjacent road section, and determining road section attribute change information according to the comparison result under the condition that the difference of the comparison results accords with the specified condition.
The link-related basic information may include at least one of link identification information, link length information, link name information, link type information, link class information, and adjacent link information. The road section related basic information of the current road section can be compared with the road section related basic information of the adjacent road section, and the road section attribute changing risk of the current road section can be determined under the condition that the difference meets the specified condition. For example, the difference meeting the specified condition may include: the speed limit of the current road section is 60 km/h, and the speed limit of the adjacent road section is 80 km/h, so that the risk of road section attribute change of the current road section can be determined. The corresponding link attribute change information may be "speed limit change", "speed limit is raised from 60 to 80", or the like. For another example, the difference meeting the specified condition may include: in the case that the current road segment is the main road and the adjacent road segment is the (exit or entrance) ramp, it can be determined that the current road segment has a road segment attribute changing risk. The corresponding link attribute change information may be "front road exit (entrance)", or the like.
Step S20219: and associating the current road segment with the road segment attribute change information to construct a road segment fingerprint table.
After the link attribute change information is determined, the current link may be associated with the link attribute change information. Meanwhile, the construction of the road section fingerprint table of the current road section can be completed.
In one embodiment, determining the target link from the candidate links using the link fingerprint table of the candidate links referred to in step S202 may include:
step S301: filtering the candidate road segments by using the road segment related risk information recorded in the road segment fingerprint table of the candidate road segments to obtain filtered candidate road segments; the link-related risk information includes risk type information or risk-free type information.
After the candidate segments are determined, a segment fingerprint table of the candidate segments may be consulted. If the link-related risk information of the candidate link is the risk-free type information recorded in the link fingerprint table, the candidate link may be deleted. Conversely, if the link-related risk information of the candidate link is information of a risky type, the link may be reserved. By filtering the candidate road segments, the data volume can be effectively reduced.
Step S302: searching in the filtered candidate road segments by utilizing a preset road segment searching strategy to determine a target road segment; the predetermined road segment search strategy is used to indicate at least one of a historical track and a navigation path of the target vehicle.
The road segment search strategy may be used to indicate a historical track or navigation path of the target vehicle. The road segment search policy may be a breadth-first search policy. Without a navigation path, the travel direction of the target vehicle, as well as the future drivable region, can be determined using the historical trajectory of the target vehicle. Based on this, the link corresponding to the future drivable area can be determined as the target link. The target link may be one link or a plurality of links.
In the case where the navigation path exists, the link indicated by the navigation path may be regarded as the target link based on the navigation path. Alternatively, in the case where a navigation path exists, the history track and the navigation path may be referred to at the same time. A travel record of the target vehicle is determined based on the historical track, and a link indicated by the navigation path is taken as a target link based on the navigation path and the travel record.
In one embodiment, the generating the road prompt information according to the link fingerprint table and the driving state of the target link in step S203 may include:
step S2031: the distance to the target link is determined using the driving state.
Based on the positioning result of the vehicle-mounted global navigation satellite system, the positioning of the target vehicle can be realized. In the case that the target vehicle position is obtained, vehicle road matching can be further performed, and the target vehicle position is matched to a specific road section in the road network. Because each road section contains a starting position and a terminating position, the offset of the target vehicle from the starting position or the terminating position of the current road section can be further determined by adopting a hidden Markov algorithm during matching. Based on the offset, the distance between the target vehicle and the target road segment can be determined relatively accurately.
Step S2032: and acquiring a predetermined keyword from a road fingerprint table of the target road.
As already mentioned, for road segments with risk, for each risk type, a hint keyword may be stored in correspondence in the road segment fingerprint table. Based on this, predetermined keyword information may be acquired from a link fingerprint table of the target link. The keyword information may be used as the main content for constructing the road hint information.
Step S2033: and generating road prompt information based on the distance and the keywords.
And combining the distance between the target vehicle and the target road section with the keyword information to generate the road prompt information. For example, "500 meters ahead is a tunnel section", "400 meters ahead is a speed change section, the speed limit after change was 40 km/h. The front 300 meters is a ramp entrance, and vehicles are converged in.
In one embodiment, the generating the road prompt information according to the link fingerprint table and the driving state of the target link in step S203 may include:
step S2034: standard data related to the driving state is acquired from a link fingerprint table of the target link.
The standard data related to the running state may be speed limit data, data whether parking is permitted, or the like. For example, the target vehicle travels on an expressway, in which case the standard data related to the traveling state may be speed limit data. For another example, the target vehicle is parked near a shopping mall, in which case the standard data related to the running state may be data whether parking is permitted at that section. For another example, in the case where the target vehicle makes a lane change overtaking, the standard data related to the running state may be data whether the current road section allows lane change.
Step S2035: and comparing the real-time data corresponding to the running state with the standard data to obtain a comparison result.
The real-time data may be a real-time vehicle speed of the target vehicle on the expressway, a running state (running or stopped) of the target vehicle, whether the target vehicle changes lanes, or the like. And comparing the real-time data corresponding to the running state with the standard data to obtain a comparison result. For example, if the vehicle speed is 130 km/h and the standard data is 120 km/h, the comparison result is overspeed. For another example, parking near a shopping mall, and locating the area to indicate the area as a parkable area may result in the comparison being in compliance with the relevant specifications.
Step S2036: and generating road prompt information based on the comparison result.
In the case where the comparison result is overspeed, overtaking is not allowed in the overtaking section, or the like, which does not meet the relevant regulations, the road prompt information may correspond to "you have overspeed", "overtaking is prohibited here", or the like. In the case that the comparison result is in accordance with the relevant regulation, the road prompt information may be encouragement information. For example, "you can please finish parking".
As shown in connection with fig. 3, the logic for generating the road hint information may include the following:
Vehicle information is acquired. The vehicle information may be information of a plurality of vehicles, and the number of the vehicles may be tens of thousands. The description will be given taking the generation of the prompt information for one of the vehicles as an example.
Using the vehicle information, a vehicle trajectory of the vehicle may be determined. The vehicle track includes information of a current position, a current speed, and the like of the vehicle. In addition, the vehicle running state can also be determined using the vehicle information, the vehicle trajectory, and the like. The vehicle travel state may include a trip start time, a travel duration, a residence duration, a distance to target road offset, and the like.
In the case of a vehicle track, the current position of the vehicle may be matched to the road network. A road segment on which the vehicle is currently traveling is determined. In case of determining a road segment on which the vehicle is currently traveling, a road segment fingerprint table of the road segment may be called up, thereby inquiring about the condition of the current road segment and inquiring about the condition of the neighboring road segment.
And generating road prompt information according to the running state of the vehicle and the road section fingerprint table. The road hint information may include two types. The first category may be road prompt information determined by comparing real-time data corresponding to the driving state with standard data and by the obtained comparison result. For example, it may include whether overspeed, abnormal parking, and the like. The second category may be road hint information generated from keywords obtained from a road segment fingerprint table. For example, there may be included a ramp in front, a change in speed limit of a current road segment, a dangerous road segment in front of the road segment, a road side event occurring in the current road segment, and the like.
Finally, the road prompt information can be displayed and played at the vehicle-mounted terminal.
An embodiment of the present application provides a method for generating a road prompt message, and as shown in fig. 4, a flowchart of a method for broadcasting a road prompt message according to an embodiment of the present application may include:
step S401: uploading information of the vehicle; the information of the vehicle includes information detected by a sensor of the vehicle.
The information of the vehicle may be information detected by a sensor of the vehicle. For example, position information, vehicle speed information, etc., detected by an on-board global navigation satellite system may be included. In-vehicle image data detected by the in-vehicle image sensor, out-of-vehicle image data, and the like may also be included. The information of the vehicle can be uploaded to the road prompt information generating end. For example, a server of a car manufacturer, a server of a third party, or the like may be used.
Step S402: broadcasting the road prompt information generated by the received information of the response vehicle; the road prompt information is generated by utilizing a road section fingerprint table and a driving state of a target road section; the target road section is determined from the candidate road section by using a road section fingerprint table of the candidate road section; the road section fingerprint table is pre-constructed and is used for representing road section related basic information and road section related risk information of the candidate road sections; the candidate road segments and the running state are determined based on the information of the target vehicle.
After receiving the information of the vehicle, the road prompt information generating end can perform road segment matching on the vehicle based on the information of the vehicle, so that the road prompt information is generated based on the related information of the vehicle, a road segment fingerprint table of the road segment and the like. The specific generation process is the same as that described in the first embodiment, and will not be described here again.
After the road prompt information is received, the road prompt information can be displayed on a vehicle-mounted screen of the vehicle or can be played through a loudspeaker of the vehicle. Thereby achieving the purpose of informing the driver.
Corresponding to the application scene and the method of the method provided by the embodiment of the application, the embodiment of the application also provides a device for generating the road prompt information. Fig. 5 is a block diagram of a road prompt generation device according to an embodiment of the present application, where the road prompt generation device may include:
a basic information determining module 501, configured to determine a candidate road segment and a driving state of a target vehicle according to information of the target vehicle; the information of the target vehicle includes information detected by a sensor of the target vehicle;
a target link determining module 502, configured to determine a target link from the candidate links using a link fingerprint table of the candidate links; the road section fingerprint table is pre-constructed and is used for representing road section related basic information and road section related risk information of the candidate road sections;
The road prompt information generating module 503 is configured to generate the road prompt information by using the road fingerprint table and the driving status of the target road.
In one embodiment, the method further comprises a road segment fingerprint table construction module, and the road segment fingerprint table construction module may comprise:
the related information determining sub-module is used for determining road section related basic information and road section related risk information of a current road section, wherein the road section related basic information comprises at least one of road section identification information, road section length information, road section name information, road section type information, road section grade information and adjacent road section information; the road segment related risk information comprises risk type information or risk-free type information; the information with risk type comprises at least one of road side event information and road section attribute change information; the road side event information comprises information of events affecting normal traffic of the road;
and the construction execution sub-module is used for constructing a road section fingerprint table of the current road section by utilizing the road section related basic information and the road section related risk information.
In one embodiment, in a case where the link-related risk information includes road side event information, constructing the execution sub-module may include:
The area determining unit is used for determining a starting area and a termination area of the road side event according to the received information of the road side event;
the road segment set determining unit is used for determining a first road segment set matched with the starting area and a second road segment set matched with the ending area;
the road side event matching unit is used for determining a road section where a road side event occurs by utilizing the first distance and the second distance; the first distance is determined using the distance between the starting region and the road segments comprised in the first set of road segments; the second distance is determined using the distance between the termination area and the road segments included in the second set of road segments;
and the road section fingerprint table construction updating unit is used for associating the road section with the road side event to construct the road section fingerprint table.
In one embodiment, in a case where the link-related risk information includes link attribute change information, constructing the execution sub-module may include:
the risk road section determining unit is used for determining a risk road section according to the traffic history data; the historical data includes at least one of violation data and traffic accident data;
the road segment attribute change information determining unit is used for determining road segment attribute change information according to the starting point and the ending point of the risk road segment;
And the road section fingerprint table construction updating unit is used for associating the risk road sections with the road section attribute change information so as to construct the road section fingerprint table.
In one embodiment, in a case where the link-related risk information includes link attribute change information, constructing the execution sub-module may include:
the road section attribute change information determining unit is used for comparing the obtained road section related basic information of the current road section with the road section related basic information of the adjacent road section, and determining the road section attribute change information according to the comparison result when the difference of the comparison results accords with the specified condition;
and the road section fingerprint table construction updating unit is used for associating the current road section with the road section attribute change information so as to construct the road section fingerprint table.
In one implementation, the target segment determination module 502 may include:
the filtering subunit is used for filtering the candidate road segments by utilizing the road segment related risk information recorded in the road segment fingerprint table of the candidate road segments to obtain filtered candidate road segments; the road segment related risk information comprises risk type information or risk-free type information;
the target road section determining and executing subunit is used for searching in the filtered candidate road sections by utilizing a preset road section searching strategy to determine the target road sections; the predetermined road segment search strategy is used to indicate at least one of a historical track and a navigation path of the target vehicle.
In one embodiment, the road hint information generating module 503 may include:
a distance determining subunit for determining a distance from the target road section by using the driving state;
a keyword determining subunit, configured to obtain a predetermined keyword from a road segment fingerprint table of a target road segment;
and the road prompt information generation and execution sub-module is used for generating the road prompt information based on the distance and the keywords.
In one embodiment, the road hint information generating module 503 may include:
a standard data acquisition subunit, configured to acquire standard data related to a driving state from a road segment fingerprint table of a target road segment;
the comparison result generation subunit is used for comparing the real-time data corresponding to the running state with the standard data to obtain a comparison result;
and the road prompt information generation and execution sub-module is used for generating the road prompt information based on the comparison result.
Corresponding to the application scene and the method of the method provided by the embodiment of the application, the embodiment of the application also provides a broadcasting device of the road prompt information. Fig. 6 is a block diagram of a road prompt information broadcasting device according to an embodiment of the present application, which may include:
A vehicle information uploading module 601, configured to upload information of a vehicle; the information of the vehicle includes information detected by a sensor of the vehicle;
the road prompt information broadcasting module 602 is configured to broadcast the received road prompt information generated by the information of the response vehicle; the road prompt information is generated by utilizing a road section fingerprint table and a driving state of a target road section; the target road section is determined from the candidate road section by using a road section fingerprint table of the candidate road section; the road section fingerprint table is pre-constructed and is used for representing road section related basic information and road section related risk information of the candidate road sections; the candidate road segments and the running state are determined based on the information of the target vehicle.
The functions of each module in each device of the embodiments of the present application may be referred to the corresponding descriptions in the above methods, and have corresponding beneficial effects, which are not described herein.
Fig. 7 is a block diagram of an electronic device used to implement an embodiment of the present application. As shown in fig. 7, the electronic device includes: a memory 710 and a processor 720, the memory 710 having stored thereon a computer program executable on the processor 720. The processor 720, when executing the computer program, implements the methods of the above-described embodiments. The number of memories 710 and processors 720 may be one or more.
The electronic device further includes:
and the communication interface 730 is used for communicating with external devices for data interactive transmission.
If memory 710, processor 720, and communication interface 730 are implemented independently, memory 710, processor 720, and communication interface 730 may be interconnected and communicate with each other via a bus. The bus may be an industry standard architecture (Industry Standard Architecture, ISA) bus, an external device interconnect (Peripheral Component Interconnect, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in fig. 7, but not only one bus or one type of bus.
Alternatively, in a specific implementation, if the memory 710, the processor 720, and the communication interface 730 are integrated on a chip, the memory 710, the processor 720, and the communication interface 730 may communicate with each other through internal interfaces.
The present embodiments provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods provided in the embodiments of the present application.
The embodiment of the application also provides a chip, which comprises a processor and is used for calling the instructions stored in the memory from the memory and running the instructions stored in the memory, so that the communication device provided with the chip executes the method provided by the embodiment of the application.
The embodiment of the application also provides a chip, which comprises: the input interface, the output interface, the processor and the memory are connected through an internal connection path, the processor is used for executing codes in the memory, and when the codes are executed, the processor is used for executing the method provided by the application embodiment.
It should be appreciated that the processor may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or any conventional processor or the like. It is noted that the processor may be a processor supporting an advanced reduced instruction set machine (Advanced RISC Machines, ARM) architecture.
Further alternatively, the memory may include a read-only memory and a random access memory. The memory may be volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), programmable ROM (PROM), erasable Programmable ROM (EPROM), electrically Erasable EPROM (EEPROM), or flash Memory, among others. Volatile memory can include random access memory (Random Access Memory, RAM), which acts as external cache memory. By way of example, and not limitation, many forms of RAM are available. For example, static RAM (SRAM), dynamic RAM (Dynamic Random Access Memory, DRAM), synchronous DRAM (SDRAM), double Data Rate Synchronous DRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), and Direct RAM (DR RAM).
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions in accordance with the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. Computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
Any process or method described in flow charts or otherwise herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process. And the scope of the preferred embodiments of the present application includes additional implementations in which functions may be performed in a substantially simultaneous manner or in an opposite order from that shown or discussed, including in accordance with the functions that are involved.
Logic and/or steps described in the flowcharts or otherwise described herein, e.g., may be considered a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. All or part of the steps of the methods of the embodiments described above may be performed by a program that, when executed, comprises one or a combination of the steps of the method embodiments, instructs the associated hardware to perform the method.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules described above, if implemented in the form of software functional modules and sold or used as a stand-alone product, may also be stored in a computer-readable storage medium. The storage medium may be a read-only memory, a magnetic or optical disk, or the like.
The foregoing is merely exemplary embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think of various changes or substitutions within the technical scope of the present application, which should be covered in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims (13)

1. The method for generating the road prompt information is characterized by comprising the following steps:
determining a candidate road section and a running state of a target vehicle according to information of the target vehicle; the information of the target vehicle includes information detected by a sensor of the target vehicle;
determining a target road section from the candidate road sections by utilizing a road section fingerprint table of the candidate road sections; the road section fingerprint table is pre-constructed and is used for representing road section related basic information and road section related risk information of the candidate road section;
and generating road prompt information by utilizing the road fingerprint table of the target road and the driving state.
2. The method of claim 1, wherein the road segment fingerprint table is constructed in a manner comprising:
determining road section related basic information and road section related risk information of a current road section, wherein the road section related basic information comprises at least one of road section identification information, road section length information, road section name information, road section type information, road section grade information and adjacent road section information; the road section related risk information comprises risk type information or risk-free type information; the information with risk type comprises at least one of road side event information and road section attribute change information; the road side event information comprises information of events affecting normal traffic of a road;
And constructing a road section fingerprint table of the current road section by utilizing the road section related basic information and the road section related risk information.
3. The method according to claim 2, wherein in case the link-related risk information includes road side event information, the link fingerprint table is constructed in a manner comprising:
determining a starting area and a terminating area of the road side event according to the received information of the road side event;
determining a first road segment set matched with the starting area and a second road segment set matched with the ending area;
determining a road section where the road side event occurs by using the first distance and the second distance; the first distance is determined using a distance between the starting region and a road segment included in the first set of road segments; the second distance is determined using the distance between the termination area and the road segments included in the second set of road segments;
and associating the road section with the road side event to construct the road section fingerprint table.
4. The method according to claim 2, wherein in case the link-related risk information includes link attribute change information, the link fingerprint table is constructed in a manner including:
Determining a risk road section according to the traffic history data; the history data comprises at least one of violation data and traffic accident data;
determining road section attribute change information according to the starting point and the ending point of the risk road section;
and associating the risk road segments with the road segment attribute change information to construct the road segment fingerprint table.
5. The method according to claim 2, wherein in case the link-related risk information includes link attribute change information, the link fingerprint table is constructed in a manner including:
comparing the acquired road section related basic information of the current road section with road section related basic information of the adjacent road section, and determining the road section attribute change information according to the comparison result under the condition that the difference of the comparison results accords with the specified condition;
and associating the current road section with the road section attribute change information to construct the road section fingerprint table.
6. The method of claim 1, wherein the determining the target segment from the candidate segments using the segment fingerprint table of the candidate segments comprises:
filtering the candidate road segments by utilizing road segment related risk information recorded in a road segment fingerprint table of the candidate road segments to obtain filtered candidate road segments; the road section related risk information comprises risk type information or risk-free type information;
Searching in the filtered candidate road segments by utilizing a preset road segment searching strategy to determine a target road segment; the predetermined road segment search strategy is used for indicating at least one of a historical track and a navigation path of the target vehicle.
7. The method of claim 1, wherein the generating the road hint information using the link fingerprint table of the target link and the driving status comprises:
determining a distance from the target road section by using the driving state;
acquiring a predetermined keyword from a road section fingerprint table of the target road section;
and generating the road prompt information based on the distance and the keywords.
8. The method of claim 1, wherein the generating the road hint information using the link fingerprint table of the target link and the driving status comprises:
acquiring standard data related to the driving state from a road section fingerprint table of the target road section;
comparing the real-time data corresponding to the running state with the standard data to obtain a comparison result;
and generating the road prompt information based on the comparison result.
9. The broadcasting method of the road prompt information is characterized by comprising the following steps of:
Uploading information of the vehicle; the information of the vehicle includes information detected by a sensor of the vehicle;
broadcasting the received road prompt information generated in response to the information of the vehicle; the road prompt information is generated by utilizing a road section fingerprint table and a driving state of a target road section; the target road section is determined from the candidate road section by utilizing a road section fingerprint table of the candidate road section; the road section fingerprint table is pre-constructed and is used for representing road section related basic information and road section related risk information of the candidate road section; the candidate segment and the running state are determined according to information of the target vehicle.
10. A road prompt information generation apparatus, comprising:
the basic information determining module is used for determining a candidate road section and the running state of the target vehicle according to the information of the target vehicle; the information of the target vehicle includes information detected by a sensor of the target vehicle;
the target road section determining module is used for determining a target road section from the candidate road sections by utilizing a road section fingerprint table of the candidate road sections; the road section fingerprint table is pre-constructed and is used for representing road section related basic information and road section related risk information of the candidate road section;
And the road prompt information generation module is used for generating road prompt information by utilizing the road section fingerprint table of the target road section and the driving state.
11. A broadcasting device of road prompt information, characterized by comprising the following steps:
the vehicle information uploading module is used for uploading the information of the vehicle; the information of the vehicle includes information detected by a sensor of the vehicle;
the road prompt information broadcasting module is used for broadcasting the received road prompt information generated in response to the information of the vehicle; the road prompt information is generated by utilizing a road section fingerprint table and a driving state of a target road section; the target road section is determined from the candidate road section by utilizing a road section fingerprint table of the candidate road section; the road section fingerprint table is pre-constructed and is used for representing road section related basic information and road section related risk information of the candidate road section; the candidate segment and the running state are determined according to information of the target vehicle.
12. An electronic device comprising a memory, a processor and a computer program stored on the memory, the processor implementing the method of any one of claims 1-9 when the computer program is executed.
13. A computer readable storage medium having stored therein a computer program which, when executed by a processor, implements the method of any of claims 1-9.
CN202211575346.5A 2022-12-08 2022-12-08 Road prompt information generation method, broadcasting method and device Pending CN116416790A (en)

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